CN114004212A - Data processing method, device and storage medium - Google Patents
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Abstract
The embodiment of the application discloses a data processing method, a data processing device and a storage medium, wherein the method comprises the following steps: determining target identification information of a target listed company selected by a user; acquiring a preset time interval parameter; acquiring relevant data of the target listed company according with the preset time interval parameters according to the target identification information; determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, and each content module is used for realizing at least one item of functional analysis or displaying at least one type of content; and generating a target analysis report of the target listed company according to the target content module set and the related data. By adopting the method and the device, the analysis report of the listed company meeting the actual needs of the user can be obtained, the personalized needs of the user are met, and the user experience can be improved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method, apparatus, and storage medium.
Background
At present, the analysis reports of the listed companies on the market are set by the organizations, the formats and the contents are limited, some contents in the reports are not needed by the users, and some contents are needed by the users but not in the reports, so that the users need to obtain corresponding data from a plurality of channels and then arrange the data, the research efficiency is low, and therefore, the problem of how to obtain the analysis reports of the listed companies which meet the actual needs of the users needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a data processing method, a data processing device and a storage medium, so that an analysis report of a listed company meeting the actual needs of a user can be obtained, the personalized needs of the user are met, and the user experience can be improved.
In a first aspect, an embodiment of the present application provides a data processing method, where the method includes:
determining target identification information of a target listed company selected by a user;
acquiring a preset time interval parameter;
acquiring relevant data of the target listed company according with the preset time interval parameters according to the target identification information;
determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, each content module is used for realizing at least one item of functional analysis or displaying at least one type of content, and P is a positive integer;
and generating a target analysis report of the target listed company according to the target content module set and the related data.
In a second aspect, an embodiment of the present application provides a data processing apparatus, where the apparatus includes: a first determining unit, a first obtaining unit, a second determining unit, and a generating unit, wherein,
the first determination unit is used for determining target identification information of a target listed company selected by a user;
the first obtaining unit is used for obtaining a preset time interval parameter;
the second obtaining unit is used for obtaining relevant data of the target listed company which accords with the preset time interval parameter according to the target identification information;
the second determining unit is configured to determine a target content module set of the target listed company, where the target content module set includes P content modules, each content module is configured to implement at least one function analysis or display at least one type of content, and P is a positive integer;
and the generating unit is used for generating a target analysis report of the target listed company according to the target content module set and the related data.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that the data processing method, apparatus and storage medium described in the embodiments of the present application determine the target identification information of the target listed company selected by the user, obtain the preset time interval parameter, acquiring relevant data of the target listed company which accords with preset time interval parameters according to the target identification information, determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, each content module is used for realizing at least one function analysis or displaying at least one type of content, generating a target analysis report of the target listed company according to the target content module set and the related data, the analysis report of the company on the market meeting the actual needs of the user can be finally obtained based on the time interval parameters set by the user and the corresponding content modules, the personalized needs of the user are met, and the user experience can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a data processing method provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart diagram of another data processing method provided in the embodiments of the present application;
FIG. 3 is a schematic flow chart diagram of another data processing method provided in the embodiments of the present application;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application;
fig. 5 is a block diagram of functional units of a data processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The electronic device described in the embodiment of the present application may include a smart Phone (e.g., an Android Phone, an iOS Phone, a Windows Phone, etc.), a tablet computer, a palm computer, a car data recorder, a notebook computer, a Mobile Internet device (MID, Mobile Internet Devices), or a wearable device (e.g., a smart watch, a bluetooth headset), which are merely examples, but are not exhaustive, and the electronic device may also include a server, for example, a cloud server.
The following describes embodiments of the present application in detail.
Referring to fig. 1, fig. 1 is a schematic flow chart of a data processing method according to an embodiment of the present application, and as shown in the figure, the data processing method includes:
101. target identification information of a target listed company selected by the user is determined.
In the embodiment of the present application, the target listed company may be one company or multiple companies, the target listed company may be a group company, multiple sub-companies may be located below the group company, and each sub-company may be a listed company or a non-listed company. The target identification information may include at least one of: company name, stock code, etc., without limitation.
102. And acquiring a preset time interval parameter.
The preset time interval parameter may be preset or default, and the preset time interval parameter may be a period of time. The preset time interval parameter may be a time range of 5 years before the current time. The preset time interval parameter may include a start time and an end time, and the preset time interval parameter may include at least one time period.
103. And acquiring the relevant data of the target listed company which accords with the preset time interval parameters according to the target identification information.
In the embodiment of the application, the corresponding keyword can be determined according to the target identification information, and then the database is searched according to the keyword, so as to obtain the relevant data of the target listed company which accords with the preset time interval parameter. The relevant data may include at least one of: the analysis report of the listed company, the news report of the company, the annual report of the listed company, etc., are not limited herein.
Optionally, in step 103, obtaining, according to the target identification information, relevant data of the target listed company that meets the preset time interval parameter includes:
31. determining a target keyword set according to the target identification information;
32. searching a preset database according to the target keyword set to obtain a first search result set;
33. and screening the first search result set to obtain the relevant data of the target listed company which accords with the preset time interval parameters.
In a specific implementation, the preset database may be preset or default, and the preset database may be a database of at least one security company. Different identification information may correspond to different keyword sets, and in a specific implementation, a mapping relationship between preset identification information and a keyword set may be stored in advance, and based on the mapping relationship, a target keyword set corresponding to target identification information may be determined, or at least one historical analysis report of the target listed company corresponding to the target identification information may be obtained, and keyword extraction is performed on the at least one historical analysis report, so that part or all of extracted keywords are obtained as the target keyword set.
Furthermore, a preset database can be searched according to the target keyword set to obtain a first search result set, and then the first search result set is screened to obtain related data of the target listed company which accords with the preset time interval parameters, or some data with the top rank can be selected.
Optionally, in the step 32, searching a preset database according to the target keyword set to obtain a first search result set, the method may include the following steps:
321. dividing the target keyword set into a first keyword set and a second keyword set, wherein the first keyword set is used for uniquely identifying the target listed company, and the second keyword set is a keyword except the first keyword set;
322. performing keyword combination on the first keyword set and the second keyword set to obtain K keyword sets, wherein each keyword set of the K keyword sets comprises at least one keyword in the first keyword set and the second keyword set;
323. searching the preset database according to the K keyword sets to obtain K search result sets;
324. and integrating the K search results to obtain the first search result set.
In a specific implementation, the target keyword set may be divided into a first keyword set and a second keyword set, where the first keyword set is used to uniquely identify the target listed company, the second keyword set may be a keyword other than the first keyword set, the first keyword set may include at least one keyword, and the second keyword set may include at least one keyword.
Further, the first keyword set and the second keyword set may be keyword-combined to obtain K keyword sets, K is greater than 1, each keyword set of the K keyword sets includes at least one keyword in the first keyword set and the second keyword set, since if all keywords are together, the search range is limited, so that some valuable data are omitted, the first keyword set of the target marketing company may be grasped, that is, the depth is grasped to surround the target marketing company, so as to avoid data deviation, in addition, the K keyword sets are based on the depth surrounding the target marketing company, strongly-related valuable data are deeply mined along each dimension, further, the preset database may be searched according to the K keyword sets to obtain K search result sets, and finally, the K search results may be integrated, and obtaining the first search result set, thus improving the search precision and avoiding valuable data omission.
In specific implementation, the process of searching the preset database by the K keyword sets may be executed in parallel, for example, each keyword set may correspond to one thread or process, and then, based on the thread or process corresponding to the K keyword sets, the preset database may be searched according to the K keyword sets, so that the search efficiency may be improved.
Optionally, in the step 324, the integrating the K search results to obtain the first search result set may include the following steps:
3241. performing heat sorting on the search results in each of the K search result sets, and screening the search results in each search result set according to the sorted heat to obtain K screened search result sets;
3242. and carrying out duplication removal operation on the K screening search result sets to obtain the first search result set.
In a particular implementation, each of the K search result sets may include a plurality of search results. Taking the search result set i as an example, the heat ranking may be performed on the search results in the search result set i, specifically, the heat of the keyword of each search result may be determined, then the heat of the keyword of each search result is summed to obtain the heat of each search result, then the heat ranking is performed on the heat of each search result, the search results with the top preset number or preset proportion are screened to obtain the screened search results, the preset number or preset proportion may be preset or default in the system, and the preset proportion may be understood as a ratio between the number of the search results in the screened search result set and the number of the search results in the search result set before being screened.
Furthermore, each search result set can be screened according to the sorted heat degree according to the above mode to obtain K screened search result sets, repeated search results may occur due to different dimensionality searches, and then duplicate removal operation can be performed on the K screened search result sets to obtain a first search result set.
Optionally, in the step 323, searching the preset database according to the K keyword sets to obtain K search result sets, which may include the following steps:
3231. determining the heat degree of each keyword set in the K keyword sets to obtain K heat degrees;
3232. determining a heat mean value of the K heats;
3233. determining a target search algorithm corresponding to the heat mean value according to a preset mapping relation between the heat and the search algorithm;
3234. determining search control parameters corresponding to the target search algorithm according to the K heat degrees to obtain K search control parameters;
3235. and searching the preset database according to the K keyword sets, the target search algorithm and the K search control parameters to obtain K search result sets.
In specific implementation, a mapping relationship between a preset heat and a search algorithm can be stored in advance, and then different search algorithms can be selected based on different heats. Different search algorithms may correspond to different search control parameters that are used to control the search accuracy.
Specifically, the heat degree of each keyword set in the K keyword sets can be determined to obtain K heat degrees, then the heat degree mean value of the K heat degrees is determined, and then the target search algorithm corresponding to the heat degree mean value is determined according to the mapping relation between the preset heat degree and the search algorithm, so that the search algorithms can be unified based on the heat degrees, and the search consistency is ensured.
Furthermore, the search control parameters corresponding to the target search algorithm can be further determined according to the K heat degrees to obtain K search control parameters, for example, the search control parameters corresponding to the target search algorithm corresponding to each of the K heat degrees can be determined according to a mapping relationship between preset heat degrees and the search control parameters to obtain K search control parameters, the algorithm control parameters are ensured to be adjusted in a personalized manner according to the heat degrees, high-heat content can be searched as much as possible, and finally, the preset database can be searched according to the K keyword sets, the target search algorithm and the K search control parameters to obtain K search result sets, so that consistency of the search algorithms is ensured, personalization of each dimension is also ensured, search results are converged, and more valuable search contents can be mined.
104. And determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, and each content module is used for realizing at least one function analysis or displaying at least one type of content.
In a specific implementation, P is a positive integer, and the target content module set of the target listed company may be determined by a template selected by the user, or the content module may be selected by the user. In particular implementations, each content module may be configured to implement at least one functional analysis or to present at least one type of content. In the specific implementation, the user selects the corresponding modules to combine according to the needs of the user, the reporting template of the listed company is automatically created, the inquired related content of the listed company is quickly obtained, and the research efficiency is improved.
In an embodiment of the present application, the content module may include at least one of: company basic information, market data, stockholder analysis, equity analysis, financial statements, company developmental capacity analysis, company profitability analysis, company amortization capacity analysis, financial notes, company high management information, dividend allocation, distribution, contribution, etc., without limitation.
Optionally, the step 104 of determining the target content module set of the target listed company may include the following steps:
a41, determining the target analysis report template identification selected by the user;
a42, determining the target content module set corresponding to the target analysis report template identification;
in the embodiment of the present application, different analysis report templates may correspond to different analysis report template identifiers, and the analysis report template identifier may uniquely identify the analysis report template. The mapping relationship between the preset analysis report template identification and the content module set, which may include at least one content module, may be stored in the electronic device in advance.
In specific implementation, a target analysis report template identifier selected by a user may be determined, and then a target content module set corresponding to the target analysis report template identifier may be determined according to a mapping relationship between a preset analysis report template identifier and a content module set, so that a corresponding content module may be configured based on an analysis report template selected by the user.
Optionally, the step 104 of determining the target content module set of the target listed company may include the following steps:
b41, displaying M content modules on a display interface, wherein M is an integer greater than 1;
b42, determining P content modules selected by the user from the M content modules, and taking the P content modules as the target content module set.
In specific implementation, M content modules can be displayed on a display interface, where M is an integer greater than 1, then P content modules selected by a user from the M content modules are determined, and the P content modules are used as a target content module set, that is, the content modules can also be displayed first and then selected by the user according to the needs of the user.
In specific implementation, different content modules may correspond to different display sequence numbers, and the display sequence numbers are used for sorting the content modules when generating the analysis report.
105. And generating a target analysis report of the target listed company according to the target content module set and the related data.
Each content module in the target content module set can be correspondingly provided with a related algorithm, corresponding data analysis is realized based on the corresponding algorithm, and finally, a target analysis report of a target marketing company can be generated based on an analysis result. The target analysis report may be saved in a preset format, where the preset format may be preset or default to the system, and the preset format may include at least one of the following: WORD format, PDF format, picture format, etc., without limitation.
Optionally, in step 105, generating a target analysis report of the target listed company according to the target content module set and the related data may include the following steps:
51. determining a control algorithm and a display sequence number of each content module in the target content module set;
52. processing the related data according to the control algorithm of each content module in the target content module set to obtain a processing result, and displaying the processing result on the corresponding content module to obtain at least one analysis result module;
53. and typesetting the at least one analysis result module according to the display sequence number to obtain the target analysis report.
In a specific implementation, a control algorithm and a display sequence number of each content module in the target content module set can be determined, and the control algorithm and the display sequence number of each content module can be preset.
Further, the related data can be processed according to the control algorithm of each content module in the target content module set to obtain a processing result, the processing result is displayed in the corresponding content module to obtain at least one analysis result module, and finally, the at least one analysis result module can be typeset according to the display sequence number to obtain a target analysis report.
For example, as shown in fig. 2, for a listed company selected by a user and a corresponding analyzed time interval, and simultaneously, module data of the listed company is freely combined as needed, the system automatically extracts corresponding data, and the specific flow and description are as follows:
a1, listed company for selection analysis: selecting a listed company needing analysis according to research needs;
a2, setting time intervals of analysis data: according to the research needs, a data interval of a listed company needing to be researched can be set, such as data of the last 5 years of research;
a3, self-defining the content of the modules of the public company: the back end of the system is internally provided with N kinds of module contents, such as company basic information, market data, stockholder analysis, capital analysis, financial statements, company development capability analysis, company profitability analysis, company repayment capability analysis, financial remarks, company high management information, bonus distribution, share sharing and the like, and a user can freely select the required module contents according to the requirements;
a4, automatically generating an analysis report of a listed company: according to the listed company module content of the user-defined combination, the back end of the system automatically extracts corresponding data to fill the module data according to the listed company name and the time interval, and stores the data in a word form, so that the user can directly modify the data when performing more in-depth analysis subsequently.
For example, for a custom "biddie" analysis report, the analysis data interval 2016-:
b1, selection of marketed company "002594-BYD";
b2, setting an analysis data time interval 2016-2020;
b3, selecting basic information of the module company, analyzing the profitability of the company and analyzing the capital stock;
and B4, automatically extracting corresponding data according to the names of listed companies and time intervals, filling the data in three modules, and storing the data in a word form.
The embodiment of the application provides the customized combination of different module contents of the listed companies, so that a user can conveniently select corresponding modules to combine according to own needs, data do not need to be acquired from a plurality of channels and are sorted, in addition, the customized combination of the module contents of the listed companies can be used for automatically generating the analysis reports of the listed companies, and further, the customized combination of different module contents of the listed companies can be used for generating the analysis reports of the listed companies so as to meet the personalized requirements of the user.
It can be seen that, in the data processing method described in the embodiment of the present application, target identification information of a target listed company selected by a user is determined, a preset time interval parameter is obtained, relevant data of the target listed company meeting the preset time interval parameter is obtained according to the target identification information, a target content module set of the target listed company is determined, the target content module set includes P content modules, each content module is used for implementing at least one item of functional analysis or displaying at least one type of content, a target analysis report of the target listed company is generated according to the target content module set and the relevant data, an analysis report of the listed company meeting actual needs of the user can be finally obtained based on the time interval parameter set by the user and the corresponding content module, personalized needs of the user are met, and user experience can be improved.
Referring to fig. 3, in accordance with the embodiment shown in fig. 1, fig. 3 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and is applied to an electronic device, as shown in the figure, the data processing method includes:
301. target identification information of a target listed company selected by the user is determined.
302. And acquiring a preset time interval parameter.
303. And acquiring the relevant data of the target listed company which accords with the preset time interval parameters according to the target identification information.
304. Determining the target analysis report template identification selected by the user.
305. And determining a target content module set corresponding to the target analysis report template identification, wherein the target content module set comprises P content modules, and each content module is used for realizing at least one item of functional analysis or displaying at least one type of content.
306. And generating a target analysis report of the target listed company according to the target content module set and the related data.
For the detailed description of steps 301 to 306, reference may be made to corresponding steps of the data processing method described in fig. 1, and details are not repeated here.
It can be seen that, the data processing method described in the embodiment of the present application determines target identification information of a target listed company selected by a user, acquires a preset time interval parameter, acquires relevant data of the target listed company conforming to the preset time interval parameter according to the target identification information, determines a target analysis report template identifier selected by the user, determines a target content module set corresponding to the target analysis report template identifier, where the target content module set includes P content modules, each content module is used to implement at least one function analysis or display at least one type of content, generates a target analysis report of the target listed company according to the target content module set and the relevant data, and can finally obtain an analysis report of the listed company conforming to the actual needs of the user based on the time interval parameter set by the user and the corresponding content module, so as to meet the personalized needs of the user, and user experience can be improved.
In accordance with the foregoing embodiments, please refer to fig. 4, where fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present application, and as shown in the drawing, the electronic device includes a processor, a memory, a communication interface, and one or more programs, which are applied to the electronic device, the one or more programs are stored in the memory and configured to be executed by the processor, and in an embodiment of the present application, the programs include instructions for performing the following steps:
determining target identification information of a target listed company selected by a user;
acquiring a preset time interval parameter;
acquiring relevant data of the target listed company according with the preset time interval parameters according to the target identification information;
determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, and each content module is used for realizing at least one item of functional analysis or displaying at least one type of content;
and generating a target analysis report of the target listed company according to the target content module set and the related data.
Optionally, in the aspect of determining the target content module set of the target listed company, the program includes instructions for performing the following steps:
determining a target analysis report template identification selected by the user;
determining the set of target content modules corresponding to the target analysis report template identification;
or,
displaying M content modules on a display interface, wherein M is an integer greater than 1;
and determining P content modules selected by the user from the M content modules, and taking the P content modules as the target content module set.
Optionally, in the aspect of generating the target analysis report of the target listed company according to the target content module set and the related data, the program includes instructions for performing the following steps:
determining a control algorithm and a display sequence number of each content module in the target content module set;
processing the related data according to the control algorithm of each content module in the target content module set to obtain a processing result, and displaying the processing result on the corresponding content module to obtain P analysis result modules;
and typesetting the P analysis result modules according to the display sequence number to obtain the target analysis report.
Optionally, in the aspect of acquiring, according to the target identification information, the relevant data of the target listed company that meets the preset time interval parameter, the program includes instructions for executing the following steps:
determining a target keyword set according to the target identification information;
searching a preset database according to the target keyword set to obtain a first search result set;
and screening the first search result set to obtain the relevant data of the target listed company which accords with the preset time interval parameters.
Optionally, in the aspect that the preset database is searched according to the target keyword set to obtain the first search result set, the program includes instructions for executing the following steps:
dividing the target keyword set into a first keyword set and a second keyword set, wherein the first keyword set is used for uniquely identifying the target listed company, and the second keyword set is a keyword except the first keyword set;
performing keyword combination on the first keyword set and the second keyword set to obtain K keyword sets, wherein each keyword set of the K keyword sets comprises at least one keyword in the first keyword set and the second keyword set;
searching the preset database according to the K keyword sets to obtain K search result sets;
and integrating the K search results to obtain the first search result set.
Optionally, in the aspect of integrating the K search results to obtain the first search result set, the program includes instructions for executing the following steps:
performing heat sorting on the search results in each of the K search result sets, and screening the search results in each search result set according to the sorted heat to obtain K screened search result sets;
and carrying out duplication removal operation on the K screening search result sets to obtain the first search result set.
Optionally, in the aspect that the preset database is searched according to the K keyword sets to obtain K search result sets, the program includes instructions for executing the following steps:
determining the heat degree of each keyword set in the K keyword sets to obtain K heat degrees;
determining a heat mean value of the K heats;
determining a target search algorithm corresponding to the heat mean value according to a preset mapping relation between the heat and the search algorithm;
determining search control parameters corresponding to the target search algorithm according to the K heat degrees to obtain K search control parameters;
and searching the preset database according to the K keyword sets, the target search algorithm and the K search control parameters to obtain K search result sets.
It can be seen that, in the electronic device described in this embodiment of the application, target identification information of a target listed company selected by a user is determined, a preset time interval parameter is obtained, related data of the target listed company meeting the preset time interval parameter is obtained according to the target identification information, a target content module set of the target listed company is determined, the target content module set includes P content modules, each content module is used for implementing at least one item of functional analysis or displaying at least one type of content, a target analysis report of the target listed company is generated according to the target content module set and the related data, an analysis report of the listed company meeting actual needs of the user can be finally obtained based on the time interval parameter and the corresponding content module set by the user, personalized needs of the user are met, and user experience can be improved.
Fig. 5 is a block diagram of functional units of a data processing apparatus 500 according to an embodiment of the present application. The data processing apparatus 500 is applied to an electronic device, and the apparatus 500 includes: a first determining unit 501, a first acquiring unit 502, a second acquiring unit 503, a second determining unit 504, and a generating unit 505, wherein,
the first determining unit 501 is configured to determine target identification information of a target listed company selected by a user;
the first obtaining unit 502 is configured to obtain a preset time interval parameter;
the second obtaining unit 503 is configured to obtain, according to the target identification information, relevant data of the target listed company that meets the preset time interval parameter;
the second determining unit 504 is configured to determine a target content module set of the target listed company, where the target content module set includes P content modules, and each content module is configured to implement at least one functional analysis or display at least one type of content;
the generating unit 505 is configured to generate a target analysis report of the target listed company according to the target content module set and the related data.
Optionally, in the aspect of determining the target content module set of the target listed company, the second determining unit 503 is specifically configured to:
determining a target analysis report template identification selected by the user;
determining the set of target content modules corresponding to the target analysis report template identification;
or,
displaying M content modules on a display interface, wherein M is an integer greater than 1;
and determining P content modules selected by the user from the M content modules, and taking the P content modules as the target content module set.
Optionally, in the aspect of generating the target analysis report of the target listed company according to the target content module set and the related data, the generating unit 505 is specifically configured to:
determining a control algorithm and a display sequence number of each content module in the target content module set;
processing the related data according to the control algorithm of each content module in the target content module set to obtain a processing result, and displaying the processing result on the corresponding content module to obtain P analysis result modules;
and typesetting the P analysis result modules according to the display sequence number to obtain the target analysis report.
Optionally, in terms of acquiring, according to the target identification information, the relevant data of the target listed company that meets the preset time interval parameter, the second acquiring unit 503 is specifically configured to:
determining a target keyword set according to the target identification information;
searching a preset database according to the target keyword set to obtain a first search result set;
and screening the first search result set to obtain the relevant data of the target listed company which accords with the preset time interval parameters.
Optionally, in the aspect of searching a preset database according to the target keyword set to obtain a first search result set, the second obtaining unit 503 is specifically configured to:
dividing the target keyword set into a first keyword set and a second keyword set, wherein the first keyword set is used for uniquely identifying the target listed company, and the second keyword set is a keyword except the first keyword set;
performing keyword combination on the first keyword set and the second keyword set to obtain K keyword sets, wherein each keyword set of the K keyword sets comprises at least one keyword in the first keyword set and the second keyword set;
searching the preset database according to the K keyword sets to obtain K search result sets;
and integrating the K search results to obtain the first search result set.
Optionally, in the aspect of integrating the K search results to obtain the first search result set, the second obtaining unit 503 is specifically configured to:
performing heat sorting on the search results in each of the K search result sets, and screening the search results in each search result set according to the sorted heat to obtain K screened search result sets;
and carrying out duplication removal operation on the K screening search result sets to obtain the first search result set.
Optionally, in the aspect that the preset database is searched according to the K keyword sets to obtain K search result sets, the second obtaining unit 503 is specifically configured to:
determining the heat degree of each keyword set in the K keyword sets to obtain K heat degrees;
determining a heat mean value of the K heats;
determining a target search algorithm corresponding to the heat mean value according to a preset mapping relation between the heat and the search algorithm;
determining search control parameters corresponding to the target search algorithm according to the K heat degrees to obtain K search control parameters;
and searching the preset database according to the K keyword sets, the target search algorithm and the K search control parameters to obtain K search result sets.
It can be seen that, the data processing apparatus described in the embodiment of the present application determines target identification information of a target listed company selected by a user, acquires a preset time interval parameter, acquires relevant data of the target listed company meeting the preset time interval parameter according to the target identification information, and determines a target content module set of the target listed company, where the target content module set includes P content modules, each content module is configured to implement at least one function analysis or display at least one type of content, and generates a target analysis report of the target listed company according to the target content module set and the relevant data, and based on the time interval parameter and the corresponding content module set by the user, an analysis report of the listed company meeting actual needs of the user is finally obtained, thereby satisfying personalized needs of the user and improving user experience.
It is to be understood that the functions of each program module of the data processing apparatus in this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the relevant description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes an electronic device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising an electronic device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method of data processing, the method comprising:
determining target identification information of a target listed company selected by a user;
acquiring a preset time interval parameter;
acquiring relevant data of the target listed company according with the preset time interval parameters according to the target identification information;
determining a target content module set of the target listed company, wherein the target content module set comprises P content modules, each content module is used for realizing at least one item of functional analysis or displaying at least one type of content, and P is a positive integer;
and generating a target analysis report of the target listed company according to the target content module set and the related data.
2. The method of claim 1, wherein determining the target set of content modules for the target listed company comprises:
determining a target analysis report template identification selected by the user;
determining the set of target content modules corresponding to the target analysis report template identification;
or,
displaying M content modules on a display interface, wherein M is an integer greater than 1;
and determining P content modules selected by the user from the M content modules, and taking the P content modules as the target content module set.
3. The method of claim 1 or 2, wherein generating the target analytics report for the target listed company from the set of target content modules and the related data comprises:
determining a control algorithm and a display sequence number of each content module in the target content module set;
processing the related data according to the control algorithm of each content module in the target content module set to obtain a processing result, and displaying the processing result on the corresponding content module to obtain P analysis result modules;
and typesetting the P analysis result modules according to the display sequence number to obtain the target analysis report.
4. The method according to claim 1 or 2, wherein the obtaining of the relevant data of the target listed company according to the target identification information comprises:
determining a target keyword set according to the target identification information;
searching a preset database according to the target keyword set to obtain a first search result set;
and screening the first search result set to obtain the relevant data of the target listed company which accords with the preset time interval parameters.
5. The method of claim 4, wherein the searching a preset database according to the target keyword set to obtain a first search result set comprises:
dividing the target keyword set into a first keyword set and a second keyword set, wherein the first keyword set is used for uniquely identifying the target listed company, and the second keyword set is a keyword except the first keyword set;
performing keyword combination on the first keyword set and the second keyword set to obtain K keyword sets, wherein each keyword set of the K keyword sets comprises at least one keyword in the first keyword set and the second keyword set;
searching the preset database according to the K keyword sets to obtain K search result sets;
and integrating the K search results to obtain the first search result set.
6. The method of claim 5, wherein the integrating the K search results to obtain the first search result set comprises:
performing heat sorting on the search results in each of the K search result sets, and screening the search results in each search result set according to the sorted heat to obtain K screened search result sets;
and carrying out duplication removal operation on the K screening search result sets to obtain the first search result set.
7. The method according to claim 5 or 6, wherein the searching the preset database according to the K keyword sets to obtain K search result sets comprises:
determining the heat degree of each keyword set in the K keyword sets to obtain K heat degrees;
determining a heat mean value of the K heats;
determining a target search algorithm corresponding to the heat mean value according to a preset mapping relation between the heat and the search algorithm;
determining search control parameters corresponding to the target search algorithm according to the K heat degrees to obtain K search control parameters;
and searching the preset database according to the K keyword sets, the target search algorithm and the K search control parameters to obtain K search result sets.
8. A data processing apparatus, characterized in that the apparatus comprises: a first determining unit, a first obtaining unit, a second determining unit, and a generating unit, wherein,
the first determination unit is used for determining target identification information of a target listed company selected by a user;
the first obtaining unit is used for obtaining a preset time interval parameter;
the second obtaining unit is used for obtaining relevant data of the target listed company which accords with the preset time interval parameter according to the target identification information;
the second determining unit is configured to determine a target content module set of the target listed company, where the target content module set includes P content modules, each content module is configured to implement at least one function analysis or display at least one type of content, and P is a positive integer;
and the generating unit is used for generating a target analysis report of the target listed company according to the target content module set and the related data.
9. An electronic device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps of the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-7.
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Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115470754A (en) * | 2022-09-19 | 2022-12-13 | 北京火山引擎科技有限公司 | Data analysis method and device, computer readable medium and electronic equipment |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108846592A (en) * | 2018-07-11 | 2018-11-20 | 北京神州泰岳软件股份有限公司 | A kind of valuation of enterprise report-generating method and device based on big data |
CN109409677A (en) * | 2018-09-27 | 2019-03-01 | 深圳壹账通智能科技有限公司 | Enterprise Credit Risk Evaluation method, apparatus, equipment and storage medium |
CN111639200A (en) * | 2020-05-29 | 2020-09-08 | 上海乂学教育科技有限公司 | Data report generation method and system based on artificial intelligence |
CN113076731A (en) * | 2021-04-28 | 2021-07-06 | 企查查科技有限公司 | Report file generation method and device, computer equipment and storage medium |
CN113297345A (en) * | 2021-05-21 | 2021-08-24 | 深圳市智尊宝数据开发有限公司 | Analysis report generation method, electronic equipment and related product |
-
2021
- 2021-12-30 CN CN202111643632.6A patent/CN114004212B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108846592A (en) * | 2018-07-11 | 2018-11-20 | 北京神州泰岳软件股份有限公司 | A kind of valuation of enterprise report-generating method and device based on big data |
CN109409677A (en) * | 2018-09-27 | 2019-03-01 | 深圳壹账通智能科技有限公司 | Enterprise Credit Risk Evaluation method, apparatus, equipment and storage medium |
CN111639200A (en) * | 2020-05-29 | 2020-09-08 | 上海乂学教育科技有限公司 | Data report generation method and system based on artificial intelligence |
CN113076731A (en) * | 2021-04-28 | 2021-07-06 | 企查查科技有限公司 | Report file generation method and device, computer equipment and storage medium |
CN113297345A (en) * | 2021-05-21 | 2021-08-24 | 深圳市智尊宝数据开发有限公司 | Analysis report generation method, electronic equipment and related product |
Non-Patent Citations (2)
Title |
---|
ABBA SUGANDA GIRSANG ET AL.: "Business Intelligence for Construction Company Acknowledgement Reporting System", 《2018 INDONESIAN ASSOCIATION FOR PATTERN RECOGNITION INTERNATIONAL CONFERENCE (INAPR)》 * |
姜小玲 等: "基于智能分析报告的指标看板设计与研究", 《电子世界》 * |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN115470754A (en) * | 2022-09-19 | 2022-12-13 | 北京火山引擎科技有限公司 | Data analysis method and device, computer readable medium and electronic equipment |
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