CN111311201A - Intelligent project matching analysis tool and implementation method thereof - Google Patents
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Abstract
The invention discloses an intelligent project matching analysis tool and an implementation method thereof, which are characterized in that a characteristic set associated with a target enterprise is identified; obtaining one or more characteristics of the set of characteristics that a subset of enterprises is associated with the target enterprise; determining that each business in the subset of businesses declares a final status for a particular project; obtaining a threshold value of the specific item, and calculating a recommendation score of the specific item for the target enterprise; if the recommendation score of the target enterprise is determined to meet or exceed a threshold value, recommending the specific item for the target enterprise; if the recommendation score of the target enterprise is determined not to exceed the threshold, the specific item is prevented from being recommended for the target enterprise, other items are recommended for the target enterprise, so that the item passing rate to be declared by the enterprise is pre-judged, and the success rate of declaring the items is improved.
Description
Technical Field
The invention relates to the technical field of computer management, in particular to an intelligent project matching analysis tool and an implementation method thereof.
Background
The project declaration refers to a series of preferential policies made by government organs for enterprises, and the enterprises write declaration files according to the government policies and then declare according to related declaration requirements and processes. When different projects are declared, the difficulty is different because the qualification and the condition of the enterprise are different.
Therefore, when an enterprise submits a project, the project can be checked for conformity with the declaration qualification and whether the declaration condition reaches the requirement for multiple times, and the operation flow is complex.
Disclosure of Invention
The invention aims to provide an intelligent project matching analysis tool and an implementation method thereof, and aims to solve the technical problems that whether a project can meet declaration qualification and whether declaration conditions are met and the project needs to be examined and checked for many times when an enterprise declares the project in the prior art, and the operation flow is complex.
In order to achieve the purpose, the invention adopts an implementation method of intelligent project matching analysis, which identifies a characteristic set associated with a target enterprise;
obtaining one or more characteristics of the set of characteristics that a subset of businesses is associated with the target business, wherein the subset of businesses is selected from a plurality of businesses that claim a particular project;
determining that each business in the subset of businesses declares a final state for a particular project, wherein the final state includes a change to a different project, an exit from the particular project, or a passage through the particular project;
obtaining a threshold value of the specific item, and calculating a recommendation score of the specific item for the target enterprise;
if the recommendation score of the target enterprise is determined to meet or exceed a threshold value, recommending the specific item for the target enterprise;
and if the recommendation score of the target enterprise is determined not to exceed the threshold, avoiding recommending the specific item for the target enterprise and recommending other items for the target enterprise.
Wherein, before obtaining the threshold value of the specific item, one or more of the following items are further included:
analyzing a plurality of characteristics determined by the plurality of businesses to determine from the plurality of characteristics the set of characteristics relevant to whether the plurality of businesses changed to a different item, passed the particular item, or exited the particular item;
determining a set of application metrics necessary to complete the particular project;
determining a number of application targets completed by the target enterprise in a set of application targets necessary to complete the particular project.
Wherein the target business calculating the recommendation score for the particular item is further based on one or more of:
the cost that the target enterprise will incur to complete the particular project;
the amount of time it will take for the target business to complete the particular project;
an amount of financial subsidization available to the target enterprise;
the degree of association of the particular item with other items.
Wherein, prior to recommending other items for the target business,
analyzing the information of the specific project and other projects to obtain field words;
generating a project domain matrix about the domain word based on a latent semantic indexing vector space model;
and matching and calculating the similarity of the specific item and other items, and generating other item sequences corresponding to the specific item according to the result of matching and calculating.
Wherein the target enterprise is to group the plurality of items into one of a plurality of recommended items or a plurality of non-recommended items;
displaying the plurality of recommended specific items simultaneously in a graphical user interface of the target enterprise;
simultaneously displaying, in the graphical user interface, an amount of financial funding available in association with each of the plurality of recommended particular items.
Wherein the likelihood of success associated with each of the plurality of recommended particular items is displayed simultaneously in the graphical user interface of the target enterprise.
The invention also provides an intelligent project matching analysis tool, which comprises: one or more hardware processors: a non-transitory computer-readable medium containing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform an implementation of the intelligent item matching analysis.
The invention relates to an intelligent project matching analysis tool and an implementation method thereof, which are characterized in that a characteristic set associated with a target enterprise is identified; obtaining one or more characteristics of the set of characteristics that a subset of enterprises is associated with the target enterprise; determining that each business in the subset of businesses declares a final status for a particular project; obtaining a threshold value of the specific item, and calculating a recommendation score of the specific item for the target enterprise; if the recommendation score of the target enterprise is determined to meet or exceed a threshold value, recommending the specific item for the target enterprise; if the recommendation score of the target enterprise is determined not to exceed the threshold, the specific item is prevented from being recommended for the target enterprise, other items are recommended for the target enterprise, so that the item passing rate to be declared by the enterprise is pre-judged, and the success rate of declaring the items is improved.
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In order to more clearly illustrate the embodiments of the present invention 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 invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an intelligent project matching analysis tool and method of implementing the same of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
In the description of the present invention, it is to be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, and are used merely for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, are not to be construed as limiting the present invention. Further, in the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
Referring to fig. 1, the present invention provides a method for implementing intelligent project matching analysis, including the following steps:
s100: identifying a set of characteristics associated with a target enterprise;
the method comprises the steps of learning the characteristics of a project to be declared by a target enterprise, searching the characteristics associated with the target enterprise in a database according to the characteristics of the target enterprise according to the learned characteristics, and accordingly performing identification set alignment on a plurality of enterprises which are associated with the target enterprise and declare a specific project and the characteristics of the enterprises which declare the specific project to generate an associated characteristic set.
S200: obtaining one or more characteristics of the set of characteristics that a subset of businesses is associated with the target business, wherein the subset of businesses is selected from a plurality of businesses that claim a particular project;
wherein the subset of businesses is selected from a plurality of businesses that claim a particular project based on an associated feature set that is aggregated across an entire list of businesses, and the selected subset of businesses has a feature or features associated with the target business.
S300: determining that each business in the subset of businesses declares a final state for a particular project, wherein the final state includes a change to a different project, an exit from the particular project, or a passage through the particular project;
according to the obtained characteristic or characteristics associated with the target enterprise, the database is further searched reversely for the final result of each enterprise declaring a specific item, whether the corresponding enterprise changes to a different item, quits the specific item or passes the specific item is judged, and the final state result is subjected to statistical recording.
S400: analyzing a plurality of characteristics determined by the plurality of businesses to determine from the plurality of characteristics the set of characteristics relevant to whether the plurality of businesses changed to a different item, passed the particular item, or exited the particular item;
wherein the deep analysis is performed based on whether the corresponding plurality of businesses have changed to different projects, exited the specific project, or passed the statistical result of the specific project. If a plurality of enterprises change to other different projects, analyzing the reason and the characteristics of each enterprise changing to other projects, and collecting and storing the reasons and the characteristics; if a plurality of enterprises pass through the specific project, analyzing the passing of each enterprise based on a certain reason and characteristic, and collecting and storing the passing; if a plurality of enterprises quit the specific project, analyzing that each enterprise quits based on a certain reason and characteristic; analyzing the plurality of characteristics determined by the plurality of enterprises by combining the analysis results and the characteristics obtained from the three different final states, thereby more accurately determining the characteristic set related to whether the plurality of enterprises change to different projects, pass through the specific project or quit the specific project.
S500: determining a set of application metrics necessary to complete the particular project;
and on the basis that a plurality of enterprises pass the specific project, screening the application indexes required by each enterprise to complete the specific project, counting and comparing all the screened application indexes, selecting the application indexes with more and repeated quantity, and rejecting a few unrepeated application indexes, thereby searching, analyzing and determining the set of the application indexes necessary for completing the specific project.
S600: determining a number of application targets completed by the target enterprise in a set of application targets necessary to complete the particular project;
based on the industry, size, and capital in which the target enterprise is located, the target enterprise then needs to complete the number of application targets based on the set of application targets necessary for the particular project.
S700: obtaining a threshold value of the specific item, and calculating a recommendation score of the specific item for the target enterprise;
if the recommendation score of the target enterprise is determined to meet or exceed a threshold value, recommending the specific item for the target enterprise;
and if the recommendation score of the target enterprise is determined not to exceed the threshold, avoiding recommending the specific item for the target enterprise and recommending other items for the target enterprise.
Wherein the target business calculating the recommendation score for the particular item is further based on one or more of: the cost that the target enterprise will incur to complete the particular project; the amount of time it will take for the target business to complete the particular project; an amount of financial subsidization available to the target enterprise; the degree of association of the particular item with other items. If the cost caused by the completion of the specific project by the target enterprise is lower than the preset cost threshold value; the amount of time that the target business will take to complete the particular project is below the preset threshold amount of time; if the degree of association between the specific item and other items is higher than the preset threshold value of the degree of association, the recommendation score of the target enterprise meets or exceeds the threshold value, and the specific item is recommended to the target enterprise; otherwise, the recommendation score of the target enterprise does not exceed the threshold, so that the specific item is prevented from being recommended for the target enterprise, and other items are recommended for the target enterprise.
Simultaneously, before recommending other items for the target enterprise, analyzing the information of the specific item and the information of the other items to obtain field words; comparing and analyzing data information of a specific project and data information of other projects through a database to obtain keywords of the industry field of the target enterprise, and then generating a project field matrix related to the field words according to a recessive word sense indexing vector space model extended by the keywords; and matching and calculating the similarity of the specific item and other items, and generating other item sequences corresponding to the specific item according to the result of matching and calculating.
Grouping a plurality of items into one of a plurality of recommended items or a plurality of non-recommended items for the target enterprise; displaying the plurality of recommended specific items simultaneously in a graphical user interface of the target enterprise; simultaneously displaying, in the graphical user interface, an amount of financial funding available in association with each of the plurality of recommended particular items. A likelihood of success associated with each of the plurality of recommended particular items is displayed simultaneously in a graphical user interface of the target enterprise. Therefore, the problems that whether the project can meet the declaration qualification and whether the declaration condition meets the requirement of multiple times of examination and check and the operation flow is complex when the enterprise declares the project in the prior art are solved, and the success rate of the declared project is improved by pre-judging the project passing rate to be declared by the enterprise.
The invention also provides an intelligent project matching analysis tool, which comprises: one or more hardware processors: a non-transitory computer-readable medium containing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform an implementation of the intelligent item matching analysis.
The processor is STM8S903K3T6C, and is a small and perfect micro-computing system formed by integrating functions (possibly including a display driving circuit, a pulse width modulation circuit, an analog multiplexer, an A/D converter and other circuits) of a central processing unit CPU, a random access memory RAM, a read-only memory ROM, various I/O ports, an interrupt system, a timer/counter and the like with data processing capacity on a silicon chip by adopting a super-large scale integrated circuit technology.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. An implementation method of intelligent project matching analysis is characterized by identifying a characteristic set associated with a target enterprise;
obtaining one or more characteristics of the set of characteristics that a subset of businesses is associated with the target business, wherein the subset of businesses is selected from a plurality of businesses that claim a particular project;
determining that each business in the subset of businesses declares a final state for a particular project, wherein the final state includes a change to a different project, an exit from the particular project, or a passage through the particular project;
obtaining a threshold value of the specific item, and calculating a recommendation score of the specific item for the target enterprise;
if the recommendation score of the target enterprise is determined to meet or exceed a threshold value, recommending the specific item for the target enterprise;
and if the recommendation score of the target enterprise is determined not to exceed the threshold, avoiding recommending the specific item for the target enterprise and recommending other items for the target enterprise.
2. The method of claim 1, wherein obtaining the threshold value for a particular item further comprises one or more of:
analyzing a plurality of characteristics determined by the plurality of businesses to determine from the plurality of characteristics the set of characteristics relevant to whether the plurality of businesses changed to a different item, passed the particular item, or exited the particular item;
determining a set of application metrics necessary to complete the particular project;
determining a number of application targets completed by the target enterprise in a set of application targets necessary to complete the particular project.
3. The implementation method of claim 1, wherein the target business calculating the recommendation score for the particular item is further based on one or more of:
the cost that the target enterprise will incur to complete the particular project;
the amount of time it will take for the target business to complete the particular project;
an amount of financial subsidization available to the target enterprise;
the degree of association of the particular item with other items.
4. The implementation method of claims 1-3, wherein before recommending other items for the target enterprise,
analyzing the information of the specific project and other projects to obtain field words;
generating a project domain matrix about the domain word based on a latent semantic indexing vector space model;
and matching and calculating the similarity of the specific item and other items, and generating other item sequences corresponding to the specific item according to the result of matching and calculating.
5. The method of claim 4, wherein a plurality of items are grouped into one of a plurality of recommended items or a plurality of non-recommended items for the target enterprise;
displaying the plurality of recommended specific items simultaneously in a graphical user interface of the target enterprise;
simultaneously displaying, in the graphical user interface, an amount of financial funding available in association with each of the plurality of recommended particular items.
6. An implementation method as recited in claim 5, wherein the likelihood of success associated with each of the plurality of recommended particular items is displayed simultaneously in a graphical user interface of the target enterprise.
7. An intelligent project matching analysis tool, comprising: one or more hardware processors: a non-transitory computer-readable medium containing instructions that, when executed by the one or more hardware processors, cause the one or more hardware processors to perform the method of any of claims 1-6.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113641903A (en) * | 2021-08-16 | 2021-11-12 | 中投国信(北京)科技发展有限公司 | Service matching method based on artificial intelligence and server |
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| CN104375998A (en) * | 2013-08-13 | 2015-02-25 | *** | Intelligentized project matching analysis tool and implementation method thereof |
| CN104700190A (en) * | 2014-09-17 | 2015-06-10 | 国家电网公司 | Method and device for matching item and professionals |
| CN109670765A (en) * | 2017-10-17 | 2019-04-23 | 甲骨文国际公司 | Academic project recommendation |
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- 2020-03-21 CN CN202010204115.8A patent/CN111311201A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104375998A (en) * | 2013-08-13 | 2015-02-25 | *** | Intelligentized project matching analysis tool and implementation method thereof |
| CN104700190A (en) * | 2014-09-17 | 2015-06-10 | 国家电网公司 | Method and device for matching item and professionals |
| CN109670765A (en) * | 2017-10-17 | 2019-04-23 | 甲骨文国际公司 | Academic project recommendation |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113641903A (en) * | 2021-08-16 | 2021-11-12 | 中投国信(北京)科技发展有限公司 | Service matching method based on artificial intelligence and server |
| CN113641903B (en) * | 2021-08-16 | 2022-05-24 | 中投国信(北京)科技发展有限公司 | Service matching method based on artificial intelligence and server |
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