CN116681261A - Intelligent archive management control system - Google Patents
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Abstract
The invention relates to the technical field of processing systems for management, in particular to an intelligent archive management control system, which comprises an attribute information acquisition module, an importance index acquisition module, a current retrieval cost index acquisition module, an adjustment cost index acquisition module, a virtual retrieval cost index acquisition module and a normalization module, wherein the modules are mutually matched, optimal attribute information is determined when personnel archives in an archive room are normalized, and the personnel archives in the archive room are normalized according to the optimal attribute information. According to the personnel file management method and the personnel file management system, the optimal attribute information is determined, and the robot is controlled to regulate the personnel files in the archive according to the optimal attribute information, so that the borrowing efficiency of the personnel files is effectively improved, and the intelligent management of the personnel files is realized.
Description
Technical Field
The invention relates to the technical field of processing systems for management, in particular to an intelligent archive management control system.
Background
The traditional file management has low working efficiency and needs to put in a large amount of manpower and material resources. Along with the rapid development of technologies such as big data and the Internet of things, file management work is gradually changed from a previous materialization mode into intelligent and informatization, intelligent systems and equipment are put into, and implementation of high-intelligent level management is promoted. The intelligent file is based on digital files characterized by digitization, networking and management automation, and has integrated intelligent sensing and cooperative processing functions. By setting up an efficient, intelligent and unified management service platform, the file data development and utilization maximization can be realized. In the whole system of the smart city, the smart archives belong to one of subsystems, and the construction aim is to realize space-time-crossing archives resource sharing and service, so that a user can acquire required resources in one step, and the resource acquisition efficiency is improved.
In the existing intelligent file management process, a robot is used for managing files, and when borrowing personnel need to borrow a certain file, the robot arm is controlled to call the corresponding file. Meanwhile, when the mechanical arm of the robot is controlled to regulate borrowed files, the files are regulated according to a preset arrangement mode. Considering that archives are borrowed and usually have certain timeliness, namely the borrowing times of different archives can change in time, at a certain period, probably some archives are borrowed more times, and at another period, probably some archives are borrowed more times in addition, when adjusting archives in the archives room according to fixed arrangement mode, the storage position that will have the archives that is borrowed at present often is unreasonable, and then the required time of calling archives of lead to the robot is longer, the borrowing cost of robot is great, the efficiency of robot and borrowing personnel when borrowing archives has been reduced, archives management rationality is relatively poor.
Disclosure of Invention
The invention aims to provide an intelligent file management control system which is used for solving the problem that the existing intelligent file management is unreasonable, so that the file borrowing efficiency is low.
In order to solve the above technical problems, the present invention provides an intelligent archive management control system, comprising:
the attribute information acquisition module is used for: when the personnel files in the archive office are regulated, at least two kinds of attribute information of the personnel files are obtained;
the importance index acquisition module is used for: classifying all personnel files according to each type of attribute information, acquiring the number of categories corresponding to each type of attribute information and personnel files under each category, acquiring practical information of a user when inquiring the personnel files in a regular time interval in the past, and determining an importance index corresponding to each type of attribute information according to the number of categories, the personnel files under each category and the practical information;
the current retrieval cost index acquisition module is used for: acquiring all personnel files retrieved by a robot in a regular time interval in the past, acquiring actual movement cost corresponding to each personnel file retrieved by the robot, and determining a current retrieval cost index corresponding to current attribute information according to the actual movement cost;
the adjustment cost index acquisition module is used for: acquiring the adjustment cost corresponding to each personnel file in the archive room when the robot carries out normalization according to each attribute information, and determining an adjustment cost index corresponding to each attribute information according to the adjustment cost;
The imaginary retrieval cost index acquisition module is used for: after obtaining an artifact and rectifying each personal file in a file room according to each attribute information, determining a virtual retrieval cost index corresponding to each attribute information according to a virtual movement cost corresponding to each personal file retrieved in a past regular time interval;
the normalization module is used for: and determining a selection index value corresponding to each attribute information according to the current retrieval cost index, the importance index, the adjustment cost index and the imaginary retrieval cost index, determining optimal attribute information according to the selection index value, and controlling the robot to normalize personnel files in a archive according to the optimal attribute information.
Further, determining an importance index corresponding to each attribute information includes:
according to the personnel files under each category obtained by classifying the personnel files according to each attribute information, determining the difference value between the number of the personnel files under each category and the number of the personnel files under other categories, calculating the average value of all the difference values corresponding to each category, and calculating the accumulated sum of the average values corresponding to all the categories;
Determining a classification importance index corresponding to each attribute information according to the number of categories obtained by classifying all personnel files according to each attribute information and the accumulation sum, wherein the classification importance index has positive correlation with the number of the categories and has negative correlation with the accumulation sum;
according to the personnel files under each category obtained by classifying all the personnel files according to each category information, determining the number of the same personnel files contained in the personnel files under any category corresponding to the personnel files under each category corresponding to each category information and the attribute information of other categories, and the total number of all the personnel files contained under the two categories, and determining the composite importance index corresponding to each category information according to the number of the same personnel files contained and the total number of all the personnel files contained;
the practical information comprises the times of each kind of attribute information used and the probability that other attribute information is not used for inquiring after the corresponding attribute information is used for inquiring, and the practical importance index corresponding to each kind of attribute information is determined according to the times and the probability;
And determining the importance index corresponding to each attribute information according to the classification importance index, the composite importance index and the practical importance index corresponding to each attribute information, wherein the classification importance index, the composite importance index and the practical importance index are in positive correlation with the importance index.
Further, determining a composite importance index corresponding to each attribute information includes:
calculating the ratio of the number of the contained identical personnel files to the total number of the contained identical personnel files according to the number of the identical personnel files contained in the personnel files under each category corresponding to each type of attribute information and the personnel files under any type of attribute information corresponding to any other type of attribute information and the total number of the contained all personnel files under the two types;
determining the maximum value in all ratios corresponding to each category corresponding to each attribute information, carrying out negative correlation mapping on the maximum value, and determining the accumulated value of negative correlation mapping results corresponding to all categories corresponding to each attribute information as an archive classification difference index between each attribute information and any other category of attribute information;
And determining the accumulated sum of file classification difference indexes between each type of attribute information and all other types of attribute information as a composite importance index corresponding to each type of attribute information.
Further, determining a practical importance index corresponding to each attribute information includes:
the number of times of each attribute information used comprises the number of times of each attribute information used when a network is utilized to electronically inquire personnel files and the number of times of each attribute information used when an archive is utilized to physically inquire the personnel files, the probability that other attribute information is not used for inquiring after the corresponding attribute information is utilized to inquire the personnel files comprises the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files and the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files when the archive is utilized to physically inquire the personnel files;
determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is electronically inquired by using a network as a first product value, and determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is inquired by an entity in an archive room as a second product value;
And determining a practical importance index corresponding to each attribute information according to the first product value and the second product value corresponding to each attribute information, wherein the first product value and the second product value are in positive correlation with the practical importance index.
Further, determining the corresponding current retrieval cost index under the current attribute information includes:
the actual movement cost corresponding to each personal file is called by the robot, and the actual movement cost comprises the actual movement cost spent by the robot moving to the file cabinet where each personal file is located when the robot calls each personal file, the actual movement cost spent by the robot moving to the interval of the file cabinet where each personal file is located and the actual movement cost spent by the interval height of the file cabinet where each personal file is located;
and carrying out weighted summation on three actual movement costs corresponding to each personnel file searched by the robot, and determining the accumulated value of weighted summation results corresponding to all the personnel files searched by the robot in a regular time interval in the past as a current searching cost index corresponding to the current attribute information.
Further, determining an adjustment cost index corresponding to each attribute information includes:
The robot adjusts the corresponding adjustment cost when each personal file in the archive room is regulated according to each attribute information, wherein the adjustment cost comprises the adjustment cost of the archive cabinet where the corresponding file is located before and after the regulation of each personal file, the adjustment cost of the interval where the archive of the archive cabinet is located and the adjustment cost of the interval height where the archive of the archive cabinet is located;
and carrying out weighted summation on three adjustment costs corresponding to each personnel file in the archive room by the robot according to each attribute information, and determining an accumulated value of weighted summation results corresponding to the robot when the personnel files in the archive room are regulated according to each attribute information as an adjustment cost index corresponding to each attribute information.
Further, a calculation formula corresponding to the selection index value corresponding to each attribute information is determined as follows:
wherein ,is->Selection index value corresponding to the species attribute information, < +.>Is->Importance index corresponding to seed attribute information, +.>Is->Imaginary retrieval cost index corresponding to the species attribute information, < ->For the corresponding current retrieval cost index under the current attribute information,/a method for retrieving the cost index is provided>Is->And adjusting cost indexes corresponding to the attribute information, wherein I is an absolute value function.
Further, determining optimal attribute information includes:
and determining the attribute information corresponding to the maximum selection index value as the optimal attribute information.
Further, the attribute information includes at least two of the following: name, gender, department, time of job entry, academy, and whether local.
The invention has the following beneficial effects: in order to realize intelligent management of personnel files, when personnel files in a archive are required to be regulated, namely reclassified and tidied, all the personnel files in the archive are classified according to different attribute information, classification conditions are analyzed, meanwhile, the attribute information conditions used by a user for inquiring the personnel files in the archive in a near stage are analyzed, and an importance index corresponding to each attribute information is determined by combining two analysis results, wherein the importance index characterizes the importance degree of classifying the personnel files in the archive by using the corresponding attribute information. And analyzing the cost size of the personnel files retrieved by the near-stage user to determine a current retrieval cost index corresponding to the current attribute information when classifying all the personnel files in the archive, wherein the current retrieval cost index characterizes the cost size of the personnel files retrieved by the near-stage user, and when the cost is larger, the current attribute information is unreasonable, and the personnel files in the archive should be reclassified more regularly. Since a certain adjustment cost is also required when the robot is controlled to reclassify the personnel files in the archive, the adjustment cost corresponding to each personnel file in the archive is analyzed according to each attribute information by the robot, and an adjustment cost index corresponding to each attribute information is determined, wherein the adjustment cost index represents the size of the adjustment cost spent when each personnel file in the archive is normalized according to the corresponding attribute information, and when the adjustment cost is smaller, the fact that each personnel file in the archive should be normalized by using the corresponding attribute information is indicated. Finally, if the personnel files in the archive room are reclassified and normalized according to each attribute information, based on the reclassification and normalization result, the borrowing cost of the robot is analyzed for the same personnel files called by the near-stage user, and a virtual retrieval cost index corresponding to each attribute information is determined, wherein the virtual retrieval cost index indicates the borrowing cost condition of the robot after reclassifying the personnel files in the archive room according to the corresponding attribute information, and the smaller the borrowing cost is, the more the corresponding attribute information should be used for normalizing each personnel file in the archive room. Finally, the current retrieval cost index, the importance index, the adjustment cost index and the imaginary retrieval cost index of each attribute information are comprehensively considered, the optimal attribute information is determined, and the robot is controlled to regulate personnel files in the archive according to the optimal attribute information, so that the cost of the robot for borrowing the personnel files is reduced, and the efficiency of the user for borrowing the personnel files is improved. According to the method and the device for the personnel file management, the optimal attribute information is determined, and the control robot is controlled to regulate the personnel file in the archive according to the optimal attribute information, so that the cost of the robot for borrowing the personnel file can be obviously reduced, the borrowing efficiency of the personnel file is effectively improved, and the intelligent management of the personnel file is realized.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an intelligent archive management control system according to the present invention;
FIG. 2 is a flowchart of a smart file management control method according to the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the present invention to achieve the preset purpose, the following detailed description is given below of the specific implementation, structure, features and effects of the technical solution according to the present invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. In addition, all parameters or indices in the formulas referred to herein are values after normalization that eliminate the dimensional effects.
The embodiment provides an intelligent archive management control system, which is composed of modules for realizing corresponding functions, and a corresponding structural schematic diagram is shown in fig. 1. The core of the system is to implement an intelligent file management control method, wherein each module in the system corresponds to each step in the method, and a flow chart corresponding to the method is shown in fig. 2. The various modules of the system are described in detail below in connection with specific steps in the method.
As shown in FIG. 1, the intelligent archive management control system comprises the following modules:
the attribute information acquisition module is used for: and when the personnel files in the archive office are regulated, acquiring at least two kinds of attribute information of the personnel files.
When using the robot arm to call each personnel file in the wisdom archival space, in order to reduce the required cost when the robot calls personnel file, improve the efficiency when the robot calls personnel file, need regularly carry out the regularity to the personnel file in the wisdom archival space. The regular purpose is, adjust the position of archives personnel archives, with the archives that is most easy borrow that borrow the number of times is many arrange the archives that comparatively conveniently call to the archives in the position, be close the archives gate promptly and be close the position of filing cabinet below to this reduces the cost of borrowing that the robot called archives, improves the user and borrows personnel's borrowing efficiency promptly, thereby realizes the wisdom management control of archives personnel archives.
In the intelligent archive management control system of the archive office, when the entity personnel archive is recorded each time, electronic archive information is recorded at the same time, wherein the electronic archive information comprises personnel electronic archive, recording and storing information corresponding to the entity personnel archive, attribute information of the personnel archive and the like, and the attribute information comprises: name, gender, department, time of job entry, academic, whether local, etc., the personnel files can be queried according to the attribute information of the personnel files.
When the robot is used for regulating personnel files in the intelligent archive office, the personnel files are classified according to the attribute information, and the classified personnel files are stored in different archive cabinets of the archive office. For example, there are a-level file cabinets in a archive, each divided into b-level, c-longitudinal compartments, each of which can hold m personal files. Before the personnel files in the archive office are currently ordered, the personnel files in the archive office are stored in a mode from top to bottom in a far-to-near mode according to the attribute information of the time of entering the personnel files, namely the personnel files with the longest time of entering the personnel files are stored in the innermost layer of the innermost filing cabinet in the archive office. Meanwhile, personnel files corresponding to the same job time are sequentially classified and arranged according to attribute information such as departments, names, sexes and the like. For example, when the personnel files are classified by name, the personnel files may be classified by the order of the initials of the names and surnames.
At least two kinds of attribute information of the personnel file need to be acquired each time the personnel file in the intelligent archive is rearranged, in this embodiment, the following various kinds of attribute information of the personnel file are acquired, including: name, gender, department, time of job entry, academy, whether local. The aim of acquiring various attribute information of the personnel file is to determine the optimal attribute information later and control the robot to adjust the position of the personnel file in the intelligent archive room according to the optimal attribute information.
The importance index acquisition module is used for: classifying all personnel files according to each type of attribute information, acquiring the number of categories corresponding to each type of attribute information and personnel files under each category, acquiring practical information of a user when inquiring the personnel files in a regular time interval in the past, and determining importance indexes corresponding to each type of attribute information according to the number of categories, the personnel files under each category and the practical information.
Classifying all personnel files in the intelligent archive according to each attribute information to obtain the number of categories corresponding to each attribute information and the personnel files under each category. For example, all personnel files in the intelligent archive office are classified according to gender, at this time, two classification categories can be obtained, at this time, the number of the categories is 2, and at the same time, personnel files under each classification category can be obtained. Meanwhile, the practical information of the user when inquiring the personnel files in the past regular time interval is obtained, and at the moment, according to the number of categories corresponding to each category of the attribute information, the personnel files under each category and the practical information, the importance index corresponding to each category of the attribute information can be determined, and the implementation steps comprise:
According to the personnel files under each category obtained by classifying the personnel files according to each attribute information, determining the difference value between the number of the personnel files under each category and the number of the personnel files under other categories, calculating the average value of all the difference values corresponding to each category, and calculating the accumulated sum of the average values corresponding to all the categories;
determining a classification importance index corresponding to each attribute information according to the number of categories obtained by classifying all personnel files according to each attribute information and the accumulation sum, wherein the classification importance index has positive correlation with the number of the categories and has negative correlation with the accumulation sum;
according to the personnel files under each category obtained by classifying all the personnel files according to each category information, determining the number of the same personnel files contained in the personnel files under any category corresponding to the personnel files under each category corresponding to each category information and the attribute information of other categories, and the total number of all the personnel files contained under the two categories, and determining the composite importance index corresponding to each category information according to the number of the same personnel files contained and the total number of all the personnel files contained;
The practical information comprises the times of each kind of attribute information used and the probability that other attribute information is not used for inquiring after the corresponding attribute information is used for inquiring, and the practical importance index corresponding to each kind of attribute information is determined according to the times and the probability;
and determining the importance index corresponding to each attribute information according to the classification importance index, the composite importance index and the practical importance index corresponding to each attribute information, wherein the classification importance index, the composite importance index and the practical importance index are in positive correlation with the importance index.
Specifically, the number of categories corresponding to each attribute information and personnel files under each category are analyzed, and the classification importance index corresponding to each attribute information can be determined, wherein the classification importance index refers to the importance degree of the attribute information which is beneficial to inquiry when all personnel files in the intelligent archive are classified according to the corresponding attribute information, and when the intelligent archive is more beneficial to inquiry, the classification importance index of the corresponding attribute information is larger. For example, when classifying according to gender, only two classification categories can be obtained, and the number of elements in each classification category, namely personnel files, is too large, which is unfavorable for classifying queries, so that the classification importance index of the corresponding attribute information should be reduced later. The calculation formula of the classification importance index corresponding to each attribute information is as follows:
wherein ,for each category importance index corresponding to attribute information,/a>The number of categories, which are obtained for classifying all personal profiles according to each attribute information, +.>An average value of absolute values of differences between the number of the personnel files under the i-th category and the number of the personnel files under the other categories, which are obtained by classifying all the personnel files according to each attribute information.
The classification importance index corresponding to each attribute informationIs of the meter(s)In the calculation formula, when the number of the categories obtained by classifying all personnel files according to the corresponding attribute information is larger, the personnel files are more accurately classified, the personnel files are more conveniently searched when the personnel files are correspondingly searched, meanwhile, the number of the personnel files in each category is more similar, the classification result is more uniform, the inquiry and storage are more convenient, and the corresponding classification importance index is larger.
Meanwhile, the number of the categories corresponding to each attribute information and personnel files under each category are analyzed, and a composite importance index corresponding to each attribute information can be determined, wherein the composite importance index refers to the importance degree of finer attribute information for classifying all personnel files in an intelligent archive when the corresponding attribute information is combined with other attribute information, and the importance degree of the corresponding attribute information is larger when the classification is finer. The implementation step for determining the composite importance index corresponding to each attribute information comprises the following steps:
Calculating the ratio of the number of the contained identical personnel files to the total number of the contained identical personnel files according to the number of the identical personnel files contained in the personnel files under each category corresponding to each type of attribute information and the personnel files under any type of attribute information corresponding to any other type of attribute information and the total number of the contained all personnel files under the two types;
determining the maximum value in all ratios corresponding to each category corresponding to each attribute information, carrying out negative correlation mapping on the maximum value, and determining the accumulated value of negative correlation mapping results corresponding to all categories corresponding to each attribute information as an archive classification difference index between each attribute information and any other category of attribute information;
and determining the accumulated sum of file classification difference indexes between each type of attribute information and all other types of attribute information as a composite importance index corresponding to each type of attribute information.
Specifically, the calculation formula of the composite importance index corresponding to each attribute information is as follows:
wherein ,for the composite importance index corresponding to the nth attribute information,/a. >For file classification difference index between the ith attribute information and other ith attribute information, G is the type number of the attribute information, ++>The ratio of the number of the same personnel files contained in the personnel files under the first category corresponding to the ith category and the personnel files under the o category corresponding to the other v category information to the total number of all the personnel files contained in the two categories is given by the ratio of the number of the same personnel files contained in the personnel files under the first category corresponding to the ith category and the other v category information>The number of categories corresponding to other v-th category information, namely the number of categories obtained by classifying all personnel files according to the v-th category information,/the number of categories is the same as the number of categories obtained by classifying all personnel files according to the v-th category information>The category number of the category corresponding to the ith attribute information, namely the number of the category obtained by classifying all personnel files according to the ith attribute information, +.>In order to take the maximum function, the function is to take the maximum value of all ratios corresponding to the first category corresponding to the ith attribute information.
The composite importance index corresponding to the above-mentioned nth attribute informationIn the calculation formula of (2), ->Maximum value +_of all ratios corresponding to the first category corresponding to the nth attribute information>When the negative correlation mapping result is larger, the difference between the u-th attribute information and the v-th attribute information is larger, the personnel files can be classified more finely when the u-th attribute information and the v-th attribute information are combined, when the difference between the u-th attribute information and all other attribute information is larger, the combination of the u-th attribute information is higher, the importance of the u-th attribute information is larger, and the corresponding compound importance index is more >The larger the value of (2).
After the classification importance index and the composite importance index corresponding to each attribute information are determined in the above manner, the natural importance index corresponding to each attribute information is determined based on the classification importance index and the composite importance index, and the corresponding calculation formula is as follows:
wherein ,for the natural importance index corresponding to the nature information of the (u), the (a), the (b), the (c),>for the classification importance index corresponding to the nth attribute information,/for the fifth item>And the composite importance index corresponding to the ith attribute information.
The above-mentioned nth attribute informationCorresponding natural importance indexIn the calculation formula of (2), ->For the classification importance index of the information of the ith species acquired based on the classification effect,/for the classification importance index of the information of the ith species acquired based on the classification effect>In order to obtain the composite importance index of the ith attribute information according to the repeated difference of the classification results among different attribute information, when the classification effect corresponding to the ith attribute information is good and the difference of the classification results of other attribute information is larger, the importance of the ith attribute information is higher, and the corresponding natural importance index is more important>The larger.
Further, the method includes the steps of obtaining practical information of a user in a regular time interval in the past during a personnel file inquiry process in an intelligent archive, wherein the regular time interval in the past refers to a time period between a current time and a corresponding time when all personnel files in the intelligent archive are completed in a regular manner last time, the practical information includes the number of times of each kind of used attribute information and the probability that other attribute information is not used for inquiry after the inquiry is carried out by using the corresponding attribute information, and determining practical importance indexes corresponding to each kind of attribute information according to the practical information, and the implementation steps include:
The number of times of each attribute information used comprises the number of times of each attribute information used when a network is utilized to electronically inquire personnel files and the number of times of each attribute information used when an archive is utilized to physically inquire the personnel files, the probability that other attribute information is not used for inquiring after the corresponding attribute information is utilized to inquire the personnel files comprises the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files and the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files when the archive is utilized to physically inquire the personnel files;
determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is electronically inquired by using a network as a first product value, and determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is inquired by an entity in an archive room as a second product value;
and determining a practical importance index corresponding to each attribute information according to the first product value and the second product value corresponding to each attribute information, wherein the first product value and the second product value are in positive correlation with the practical importance index.
The system comprises a client, a server and a server, wherein, for an intelligent archive office, the server generally has two modes of borrowing personnel files, one borrowing personnel with authority directly carries out electronic inquiry on a network and retrieves the electronic personnel files, the other borrowing personnel with authority or without authority carries out entity inquiry in the intelligent archive office, and a robot is assisted to call the entity personnel files after the inquiry is completed.
Acquiring the times of the borrower for electronically inquiring personnel files by utilizing each attribute information on a network in a past regular time interval of an intelligent archive, acquiring the probability of no longer using other attribute information for inquiring after the borrower utilizes each attribute information to electronically inquire on the network, and determining the product value of the times and the probability as a first product value, wherein the first product value is a first practical importance index corresponding to each attribute information, and the corresponding calculation formula is as follows:
wherein ,for the first practical importance index corresponding to the ith attribute information,/for the first practical importance index>For the number of times of the u-th attribute information used by the user to electronically query the personal file by using the network in the regular time interval in the past in the intelligent archive, The probability that the user uses the u-th attribute information to inquire and then does not use other attribute information to inquire when the user uses the network to electronically inquire personnel files in the regular time interval in the past is provided for the intelligent archive.
In the calculation formula of the first practical importance index corresponding to the u-th attribute information, when the number of times that the user uses the u-th attribute information to electronically query the personnel file by using the network is greater, and the probability that the user does not use other attribute information to query after querying by using the u-th attribute information is greater, the higher the practicability of the current attribute information, the easier the personnel file is queried, the more important the current attribute information is, and the larger the corresponding value of the first practical importance index is.
Meanwhile, the times of entity inquiry of personnel files by borrowers in the archive room by utilizing each kind of attribute information are obtained in the past regular time interval, the probability that the borrowers do not use other attribute information to inquire after the entity inquiry of the personnel files is carried out in the archive room by utilizing each kind of attribute information is obtained, the product value of the times and the probability is determined to be a second product value, the second product value is a second practical importance index corresponding to each kind of attribute information, and the corresponding calculation formula is as follows:
wherein ,for the second practical importance index corresponding to the ith attribute information,/for the fifth item>Entity inquirer for intelligent archive office user in archive office in regular time intervalThe number of times the information of the ith category was used in the event archive,the probability that the user does not use other attribute information to query after the u-th attribute information is used for querying when the user queries the personnel file in the archive in the past regular time interval for the intelligent archive.
In the calculation formula of the second practical importance index corresponding to the u-th attribute information, when the number of times that the user uses the u-th attribute information to search the personnel file in the archive is greater, and the frequency that the user directly borrows according to the search result after searching using the u-th attribute information is greater, the higher the practicability of the current attribute information is, the easier the personnel file is searched, the more important the current attribute information is, and the larger the value of the corresponding second practical importance index is.
Based on the network query condition and the entity query condition corresponding to each attribute information, that is, based on the determined first practical importance index and the determined second practical importance index corresponding to each attribute information, determining a practical importance index corresponding to each attribute information, where the practical importance index refers to an importance degree of attribute information which is favorable for borrowing personnel to search for personnel files when all personnel files in an intelligent archive are classified according to the corresponding attribute information, and when borrowing personnel is easier to search for personnel files, the practical importance index is larger, and the corresponding calculation formula is that:
wherein ,is the practical importance index corresponding to the nth attribute information,>for the first practical importance index corresponding to the ith attribute information,/for the first practical importance index>And the second practical importance index corresponding to the ith attribute information.
The practical importance index corresponding to the above-mentioned nth attribute informationIn the calculation formula of (2), when the first practical importance index and the second practical importance index are larger, the comprehensive practicability of the current attribute information is higher, the current attribute information is more important, and the corresponding practical importance index is larger.
Based on the obtained natural importance index and practical importance index corresponding to each attribute information, determining the importance index corresponding to each attribute information, wherein the corresponding calculation formula is as follows:
wherein ,importance index corresponding to the information of the nth species,/for the information of the nth species>For the natural importance index corresponding to the nature information of the (u), the (a), the (b), the (c),>is a practical importance index corresponding to the ith attribute information.
Importance index corresponding to the above-mentioned nth attribute informationIn the calculation formula of (2), when the natural importance index and the practical importance index are larger, the natural importance of the current attribute information is larger, the practical importance is also larger, the current attribute information is more important, and the value of the corresponding importance index is larger.
The current retrieval cost index acquisition module is used for: and acquiring all personnel files retrieved by the robot in a regular time interval in the past, acquiring the actual movement cost corresponding to each personnel file retrieved by the robot, and determining the corresponding current retrieval cost index under the current attribute information according to the actual movement cost.
The method comprises the steps of acquiring all personnel files retrieved by a robot in a regular time interval in the past, wherein the robot needs to spend a certain movement cost when retrieving the personnel files, the movement cost refers to the energy cost spent by the robot, the path length of movement of the robot, the height of arm change of the robot and the like can be used for measuring, the scheme is not limited, the movement cost corresponding to each personnel file when retrieving the robot needs to be acquired, the movement cost can also be called actual movement cost, and the current retrieval cost index corresponding to the current attribute information is determined according to the actual movement cost, and the implementation steps comprise:
the actual movement cost corresponding to each personal file is called by the robot, and the actual movement cost comprises the actual movement cost spent by the robot moving to the file cabinet where each personal file is located when the robot calls each personal file, the actual movement cost spent by the robot moving to the interval of the file cabinet where each personal file is located and the actual movement cost spent by the interval height of the file cabinet where each personal file is located;
And carrying out weighted summation on three actual movement costs corresponding to each personnel file searched by the robot, and determining the accumulated value of weighted summation results corresponding to all the personnel files searched by the robot in a regular time interval in the past as a current searching cost index corresponding to the current attribute information.
Specifically, the robot defaults to store the forefront of the files in the archive, when the robot retrieves each personal file, the robot needs to move from the default position to the position of the row of the archive cabinet where the personal file is located, and the actual movement cost spent by the robot in the moving process is called the actual movement cost spent by moving to the archive cabinet where each personal file is located, and the actual movement cost can be measured by the path length of the movement of the robot. When the row of the filing cabinet where the personnel file is located is closer to the innermost part of the filing room, the farther the distance from the robot is, the larger the corresponding actual moving cost is. When the robot moves to the position of the filing cabinet where the personnel file is located, because the personnel file is stored in a certain longitudinal interval of the filing cabinet where the personnel file is located, the robot needs to move from the position of the row where the personnel file is located to the position of the interval where the personnel file is stored, and the actual moving cost spent by the robot in the moving process is called the actual moving cost spent by moving to the interval of the filing cabinet where each personnel file is located, and the actual moving cost can be measured by the path length of the movement of the robot. When the distance between the personnel files and the aisle is longer, the robot moves from the position of the row of the file cabinet where the personnel files are located to the distance between the personnel files and the aisle, and the corresponding actual moving cost is larger. When the robot moves to the position of the interval where the personnel files are stored, the interval of the filing cabinet where the personnel files are located has a certain height, so that the height of the arm of the robot needs to be adjusted to obtain the corresponding personnel files, and the cost spent by the robot in the process is called the actual moving cost spent by the interval height of the filing cabinet where each personnel file is located, and the actual moving cost can be measured by the adjustment height of the arm of the robot. When the interval height of the filing cabinet where the personnel files are located is larger, the height of the robot arm to be lifted is larger, and the corresponding actual moving cost is larger.
For each personnel file retrieved by the robot in the past regular time interval, carrying out weighted summation according to the three actual movement costs corresponding to the personnel file, and determining the accumulated value of the weighted summation results of all the personnel files retrieved by the robot in the past regular time interval as a current retrieval cost index corresponding to the current attribute information, wherein the corresponding calculation formula is as follows:
/>
wherein ,for the corresponding current retrieval cost index under the current attribute information, < ->For the weighted sum of the three actual movement costs corresponding to the nth personnel file retrieved by the robot in the past regular time interval, +.>For the total number of all personnel files retrieved by the robot during a regular time interval in the past,/->For the actual movement costs spent by the robot moving to the filing cabinet in which the nth personnel file is located when retrieving the nth personnel file in the past regular time interval +.>For the actual movement costs spent by the robot moving to the interval of the filing cabinet where the nth personnel file is located when retrieving the nth personnel file in the past regular time interval +.>For the actual movement costs spent by the robot in retrieving the nth personal file in the past regular time interval due to the space height of the file cabinet where the nth personal file is located, < > >、/> and />Respectively->、/> and />The corresponding weight value can be set according to the actual situation, in this embodiment +.>、/> and />。
Corresponding current retrieval cost index under the current attribute informationIn the calculation formula of (2), when the three actual movement costs corresponding to each personnel file are larger, the weighted sum result of the three actual movement costs corresponding to each personnel file is larger in value, which means that the retrieval cost of the corresponding personnel file is larger. When the value of the weighted sum result corresponding to each personnel file is larger, the higher the cost of retrieving the personnel file at the current stage is, the larger the corresponding current retrieval cost index is when the personnel files in the intelligent archive room are classified according to the current attribute information.
The adjustment cost index acquisition module is used for: and acquiring the adjustment cost corresponding to each personnel file in the archive room when the robot carries out normalization according to each attribute information, and determining an adjustment cost index corresponding to each attribute information according to the adjustment cost.
The personnel files in the intelligent archive office are classified according to different attribute information, different classification results are obtained, and the robot is used for adjusting the personnel files, so that different adjustment costs can be obtained. In order to facilitate the subsequent determination of the optimal attribute information, on the basis of the position of the personnel file in the archive corresponding to the current attribute information, the personnel file in the archive is reclassifying and regularizing according to each attribute information, the adjustment cost corresponding to the time of the robot reclassifying each personnel file in the archive according to each attribute information is obtained, the adjustment cost is analyzed, and the adjustment cost index corresponding to each attribute information is determined, wherein the implementation steps comprise:
The robot adjusts the corresponding adjustment cost when each personal file in the archive room is regulated according to each attribute information, wherein the adjustment cost comprises the adjustment cost of the archive cabinet where the corresponding file is located before and after the regulation of each personal file, the adjustment cost of the interval where the archive of the archive cabinet is located and the adjustment cost of the interval height where the archive of the archive cabinet is located;
and carrying out weighted summation on three adjustment costs corresponding to each personnel file in the archive room by the robot according to each attribute information, and determining an accumulated value of weighted summation results corresponding to the robot when the personnel files in the archive room are regulated according to each attribute information as an adjustment cost index corresponding to each attribute information.
Specifically, on the basis of the position of the personnel file in the archive corresponding to the current attribute information, reclassifying and regularizing the personnel file in the archive according to each attribute information, determining the placement position of the personnel file in the archive after reclassifying and regularizing, and further obtaining the corresponding adjustment cost when the robot regularizes each personnel file in the archive according to each attribute information. When the personnel files in the archive office are reclassified according to each attribute information, and then a more detailed classification mode based on reclassification can be determined according to a preset mode, which is not limited, and the key point of the scheme is to determine the attribute information for first classifying the personnel files.
Because the position of the row of the filing cabinet where each personal file is located is usually different from the position of the row of the filing cabinet where the corresponding personal file is located when the personal file in the filing room is organized according to the current attribute information after the personal files in the filing room are rearranged according to each attribute information, at this time, the robot is required to adjust the personal files from the position of the row of the filing cabinet where the current attribute information corresponds to the position of the row of the filing cabinet where each attribute information corresponds to the position of the row of the filing cabinet where the corresponding personal file is located, and the moving cost spent by the robot in the moving process is called the adjusting cost of the filing cabinet where the corresponding personal file is located before and after the arrangement. The adjustment cost can be measured by the path length of the robot movement, and the larger the path length of the movement is, the higher the corresponding adjustment cost is. Meanwhile, when the position of each personal file is adjusted, the robot is required to take down each personal file from the position of the space where the current filing cabinet is stored and place the personal file at the position of the space where the filing cabinet corresponding to each kind of attribute information is stored, in the process, the moving cost spent by the robot is called the adjusting cost of the space where the filing cabinet corresponding to each personal file before and after the regulation is located because the positions of the spaces where the personal files are stored are different, and the adjusting cost can be measured by the path length of the movement of the robot. In this process, because the positions of the interval heights stored by the personnel files are different, the cost of the robot for adjusting the height of the arm is called the adjustment cost of the interval height of the file of the corresponding file cabinet before and after the regulation of each personnel file, and the adjustment cost can be measured by the adjustment height of the arm of the robot. For example, the current position of a personnel file is the 4 th row of filing cabinet, the 3 rd layer and the 3 rd longitudinal interval, assuming that the adjusted position of the personnel file is the sum of the moving costs of the 3 rd row of filing cabinet, the 3 rd layer and the 2 nd longitudinal interval, the moving cost of the robot to the position of the 4 th row of filing cabinet and the moving cost of the robot to the 3 rd row of filing cabinet is taken as the adjusting cost of the filing cabinet corresponding to the personnel file before and after the regulation, the moving cost of the robot to the 3 rd longitudinal interval of the 4 th row of filing cabinet from the position of the 4 th row of filing cabinet is taken as the moving cost of the robot to the 3 rd longitudinal interval of the 3 rd row of filing cabinet from the position of the 3 rd row of filing cabinet, and the moving cost of the robot to the 2 nd longitudinal interval of the 3 th row of filing cabinet from the position of the 3 th row of filing cabinet is taken as the accumulating sum of the moving cost of the moving costs of the moving cost of the personnel file to the 3 th longitudinal interval of the 4 th row of filing cabinet corresponding to the longitudinal interval before and after the regulation, and the moving cost of the robot to the 3 th row of filing cabinet is taken as the moving cost of the longitudinal interval of the personnel file corresponding to the 3 th row of filing cabinet after the longitudinal interval of the 3 row of filing cabinet.
After three adjustment costs corresponding to each personnel file in the archive room are obtained when the robot carries out normalization according to each attribute information, the three adjustment costs corresponding to each personnel file are weighted and summed, and the accumulated sum of weighted and summed results corresponding to all personnel files in the archive room is determined as an adjustment cost index corresponding to each attribute information, wherein the corresponding calculation formula is as follows:
wherein ,adjusting cost index corresponding to each attribute information, < > for each attribute information>Weighted sum of three adjustment costs for the g-th personal profile in the archive,/->For the total number of all personnel files in the archive +.>For each personal file in the archive office to be regulated according to each attribute information, the g-th personal file corresponds to the personal file before and after the regulationThe adjustment cost of the file cabinet where (2) is located, +.>In order to adjust the interval of the file cabinet corresponding to the g-th personal file before and after the normalization when the personal file in the archive is normalized according to each attribute information, the price is>In order to adjust the interval height of the file cabinet corresponding to the g-th personal file before and after the arrangement when the arrangement of each personal file in the archive according to each attribute information, the cost is- >、/> and />Respectively->、/> and />The corresponding weight value can be set according to the actual situation, in this embodiment +.>、/> and />。/>
The adjustment cost index corresponding to each attribute informationIn the calculation formula of (a), when eachWhen the three adjustment costs corresponding to the personnel files are larger, the weighted sum result of the three adjustment costs corresponding to the personnel files is larger in value, and the cost for adjusting the positions of the corresponding personnel files is larger. When the weighted sum result of the three adjustment costs of each personnel file in the archive room is larger, the cost for adjusting each personnel file in the archive room according to the corresponding attribute information is larger, the corresponding adjustment cost index is larger, and at the moment, the personnel files in the archive room are not adjusted by using the corresponding attribute information.
The imaginary retrieval cost index acquisition module is used for: after obtaining the false image and rectifying each personal file in the archive according to each attribute information, the robot reads the corresponding fictitious movement cost when each personal file is read in the past rectifying time interval, and the fictitious reading cost index corresponding to each attribute information is determined according to the fictitious movement cost.
And (3) reclassifying and regularizing personnel files in the archive according to each attribute information, determining the placement positions of the personnel files in the archive after reclassifying and regularizing, and further determining the corresponding fictitious movement cost when the robot reviews each personnel file reviewed in the past regular time interval. The fictitious moving cost is that after the personnel files in the archive room are reclassified and regulated according to each attribute information, for each personnel file called in the past regular time interval, the moving cost spent when the personnel file is borrowed by the robot is determined, and the acquiring process is completely consistent with the process of acquiring the actual moving cost corresponding to the robot when the personnel file is called in the current calling cost index acquiring module, which is not repeated here. After determining the imaginary moving cost corresponding to each personal file retrieved by the robot in the regular time interval in the past, corresponding to each attribute information, determining the imaginary retrieving cost index corresponding to each attribute information based on the imaginary moving cost, wherein the specific determining process is completely consistent with the process of determining the current retrieving cost index corresponding to the current attribute information based on the actual moving cost in the current retrieving cost index obtaining module, and is not repeated herein.
The normalization module is used for: and determining a selection index value corresponding to each attribute information according to the current retrieval cost index, the importance index, the adjustment cost index and the imaginary retrieval cost index, determining optimal attribute information according to the selection index value, and controlling the robot to normalize personnel files in a archive according to the optimal attribute information.
For each attribute information, according to the corresponding importance index, the adjustment cost index and the imaginary retrieval cost index, and combining the current retrieval cost index, determining a selection index value corresponding to each attribute information, wherein the corresponding calculation formula is as follows:
wherein ,is->Selection index value corresponding to the species attribute information, < +.>Is->Importance index corresponding to seed attribute information, +.>Is->Imaginary retrieval cost index corresponding to the species attribute information, < ->For the corresponding current retrieval cost index under the current attribute information,/a method for retrieving the cost index is provided>Is->And adjusting cost indexes corresponding to the attribute information, wherein I is an absolute value function.
The above-mentioned firstSelection index value corresponding to the species attribute information +.>In the calculation formula of (2), ->Based on the current attribute information classification plan, if according to +. >After the personal files in the archive office are reclassified and normalized by the personal attribute information, the robot borrows the difference value of the borrowing cost spent when the robot retrieves all the personal files in the past regular time interval. When the importance corresponding to the attribute information of a certain kind is higher, the cost of the robot for adjusting the file position is smaller, the cost of the file which is retrieved by the robot for retrieving the history after the rearrangement is smaller, and the cost difference of the file which is retrieved by the robot for the same personnel before and after the rearrangement is larger, namely, the required price is->The bigger the->Smaller (less)>Smaller (less)>The larger the personnel file is, the better the personnel file classifying and sorting effect according to the current attribute information is, and the personnel file can be retrieved more conveniently.
After the selection index value corresponding to each attribute information is determined in the above manner, the attribute information corresponding to the largest selection index value is determined as the optimal attribute information. The control robot classifies and organizes personnel files in the archive according to the optimal attribute information so as to improve the borrowing efficiency of the personnel files in the archive.
It should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (9)
1. An intelligent archive management control system, comprising:
the attribute information acquisition module is used for: when the personnel files in the archive office are regulated, at least two kinds of attribute information of the personnel files are obtained;
the importance index acquisition module is used for: classifying all personnel files according to each type of attribute information, acquiring the number of categories corresponding to each type of attribute information and personnel files under each category, acquiring practical information of a user when inquiring the personnel files in a regular time interval in the past, and determining an importance index corresponding to each type of attribute information according to the number of categories, the personnel files under each category and the practical information;
the current retrieval cost index acquisition module is used for: acquiring all personnel files retrieved by a robot in a regular time interval in the past, acquiring actual movement cost corresponding to each personnel file retrieved by the robot, and determining a current retrieval cost index corresponding to current attribute information according to the actual movement cost;
the adjustment cost index acquisition module is used for: acquiring the adjustment cost corresponding to each personnel file in the archive room when the robot carries out normalization according to each attribute information, and determining an adjustment cost index corresponding to each attribute information according to the adjustment cost;
The imaginary retrieval cost index acquisition module is used for: after obtaining an artifact and rectifying each personal file in a file room according to each attribute information, determining a virtual retrieval cost index corresponding to each attribute information according to a virtual movement cost corresponding to each personal file retrieved in a past regular time interval;
the normalization module is used for: and determining a selection index value corresponding to each attribute information according to the current retrieval cost index, the importance index, the adjustment cost index and the imaginary retrieval cost index, determining optimal attribute information according to the selection index value, and controlling the robot to normalize personnel files in a archive according to the optimal attribute information.
2. An intelligent archive management control system according to claim 1, wherein determining the importance index for each attribute information comprises:
according to the personnel files under each category obtained by classifying the personnel files according to each attribute information, determining the difference value between the number of the personnel files under each category and the number of the personnel files under other categories, calculating the average value of all the difference values corresponding to each category, and calculating the accumulated sum of the average values corresponding to all the categories;
Determining a classification importance index corresponding to each attribute information according to the number of categories obtained by classifying all personnel files according to each attribute information and the accumulation sum, wherein the classification importance index has positive correlation with the number of the categories and has negative correlation with the accumulation sum;
according to the personnel files under each category obtained by classifying all the personnel files according to each category information, determining the number of the same personnel files contained in the personnel files under any category corresponding to the personnel files under each category corresponding to each category information and the attribute information of other categories, and the total number of all the personnel files contained under the two categories, and determining the composite importance index corresponding to each category information according to the number of the same personnel files contained and the total number of all the personnel files contained;
the practical information comprises the times of each kind of attribute information used and the probability that other attribute information is not used for inquiring after the corresponding attribute information is used for inquiring, and the practical importance index corresponding to each kind of attribute information is determined according to the times and the probability;
And determining the importance index corresponding to each attribute information according to the classification importance index, the composite importance index and the practical importance index corresponding to each attribute information, wherein the classification importance index, the composite importance index and the practical importance index are in positive correlation with the importance index.
3. An intelligent archive management control system according to claim 2, wherein determining the composite importance index for each attribute information comprises:
calculating the ratio of the number of the contained identical personnel files to the total number of the contained identical personnel files according to the number of the identical personnel files contained in the personnel files under each category corresponding to each type of attribute information and the personnel files under any type of attribute information corresponding to any other type of attribute information and the total number of the contained all personnel files under the two types;
determining the maximum value in all ratios corresponding to each category corresponding to each attribute information, carrying out negative correlation mapping on the maximum value, and determining the accumulated value of negative correlation mapping results corresponding to all categories corresponding to each attribute information as an archive classification difference index between each attribute information and any other category of attribute information;
And determining the accumulated sum of file classification difference indexes between each type of attribute information and all other types of attribute information as a composite importance index corresponding to each type of attribute information.
4. An intelligent archive management control system according to claim 2, wherein determining the utility importance index for each attribute information comprises:
the number of times of each attribute information used comprises the number of times of each attribute information used when a network is utilized to electronically inquire personnel files and the number of times of each attribute information used when an archive is utilized to physically inquire the personnel files, the probability that other attribute information is not used for inquiring after the corresponding attribute information is utilized to inquire the personnel files comprises the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files and the probability that other attribute information is not used after the corresponding attribute information is utilized to inquire the personnel files when the archive is utilized to physically inquire the personnel files;
determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is electronically inquired by using a network as a first product value, and determining a product value of the frequency and the probability corresponding to each attribute information when the personnel file is inquired by an entity in an archive room as a second product value;
And determining a practical importance index corresponding to each attribute information according to the first product value and the second product value corresponding to each attribute information, wherein the first product value and the second product value are in positive correlation with the practical importance index.
5. An intelligent archive management control system according to claim 1, wherein determining a current retrieval cost indicator corresponding to the current attribute information comprises:
the actual movement cost corresponding to each personal file is called by the robot, and the actual movement cost comprises the actual movement cost spent by the robot moving to the file cabinet where each personal file is located when the robot calls each personal file, the actual movement cost spent by the robot moving to the interval of the file cabinet where each personal file is located and the actual movement cost spent by the interval height of the file cabinet where each personal file is located;
and carrying out weighted summation on three actual movement costs corresponding to each personnel file searched by the robot, and determining the accumulated value of weighted summation results corresponding to all the personnel files searched by the robot in a regular time interval in the past as a current searching cost index corresponding to the current attribute information.
6. An intelligent archive management control system according to claim 1, wherein determining an adjustment cost index for each attribute information comprises:
the robot adjusts the corresponding adjustment cost when each personal file in the archive room is regulated according to each attribute information, wherein the adjustment cost comprises the adjustment cost of the archive cabinet where the corresponding file is located before and after the regulation of each personal file, the adjustment cost of the interval where the archive of the archive cabinet is located and the adjustment cost of the interval height where the archive of the archive cabinet is located;
and carrying out weighted summation on three adjustment costs corresponding to each personnel file in the archive room by the robot according to each attribute information, and determining an accumulated value of weighted summation results corresponding to the robot when the personnel files in the archive room are regulated according to each attribute information as an adjustment cost index corresponding to each attribute information.
7. The intelligent archive management control system of claim 1, wherein the calculation formula for determining the selection index value for each attribute information is:
wherein ,is->Selection index value corresponding to the species attribute information, < +.>Is->Importance index corresponding to seed attribute information, +. >Is->Imaginary retrieval cost index corresponding to the species attribute information, < ->For the corresponding current retrieval cost index under the current attribute information,/a method for retrieving the cost index is provided>Is->And adjusting cost indexes corresponding to the attribute information, wherein I is an absolute value function.
8. An intelligent archive management control system according to claim 1, wherein determining optimal attribute information comprises:
and determining the attribute information corresponding to the maximum selection index value as the optimal attribute information.
9. An intelligent archive management control system according to claim 1, wherein the attribute information includes at least two of: name, gender, department, time of job entry, academy, and whether local.
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