CN115660391A - Scientific and technological project accurate matching system and method based on artificial intelligence and storage medium - Google Patents
Scientific and technological project accurate matching system and method based on artificial intelligence and storage medium Download PDFInfo
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Abstract
The invention relates to the technical field of artificial intelligence, in particular to a scientific and technological project accurate matching system, a scientific and technological project accurate matching method and a storage medium based on artificial intelligence, wherein the scientific and technological project accurate matching method comprises the following steps: an information acquisition step: acquiring project information and enterprise information, wherein the project information comprises: reporting condition information and success condition information; reporting and judging: judging whether the enterprise accords with the reporting condition or not according to the reporting condition information and the enterprise information, and if so, executing a success rate estimation step; a success rate estimation step: estimating the probability value of successful declaration of the enterprise according to the success condition information and the enterprise information; a probability value judging step: judging whether the probability value is greater than a first preset probability value or not, if so, executing a pushing step; a recommendation step: and pushing the project information to the enterprise. The scheme can help enterprises with reporting conditions to report proper projects, so that the success probability of reporting is improved, and resource waste is reduced.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a scientific and technological project accurate matching system and method based on artificial intelligence and a storage medium.
Background
With the increase of national and local financial support fund channels, enterprises can apply more and more financial support projects. In the last 10 years, a plurality of enterprises cultivate personnel through declaration projects, the self quality is improved, and the development speed of the enterprises is greatly improved under the comprehensive action of external cause fund support and internal cause enterprise management enhancement.
However, the current projects are generally issued through official networks, and although all the reportable projects are included, no method for helping enterprises to acquire the reportable projects through technical means exists, so that many enterprises still have the possibility that the situations of the existing reportable projects, whether the existing reportable projects have reportable conditions and whether the existing enterprises have the reportable conditions or not and successfully report the existing reportable projects; however, projects which are unknown, which meet the declaration conditions, which are missed and which have low declaration possibility of declaration results appear, and under the condition, the projects do not enjoy the support of the country and the place, and a large amount of manpower resources and time resources are wasted for applying for the projects.
Therefore, the technology project accurate matching method based on artificial intelligence is continued, and enterprises with reporting conditions can be helped to perform appropriate project reporting, so that the reporting success probability is improved, and the resource waste is reduced.
Disclosure of Invention
One of the purposes of the invention is to provide an artificial intelligence-based scientific and technological project accurate matching method, which can help enterprises with declaration conditions to perform appropriate project declaration so as to improve the probability of success declaration and reduce resource waste.
The invention provides a basic scheme I: an artificial intelligence based scientific and technological project accurate matching method comprises the following steps:
an information acquisition step: acquiring project information and enterprise information, wherein the project information comprises: reporting condition information and success condition information;
reporting and judging: judging whether the enterprise accords with the reporting condition or not according to the reporting condition information and the enterprise information, and if so, executing a success rate estimation step;
a success rate estimation step: estimating the probability value of successful declaration of the enterprise according to the success condition information and the enterprise information;
a probability value judgment step: judging whether the probability value is greater than a first preset probability value or not, if so, executing a pushing step;
a recommendation step: and pushing the project information to the enterprise.
Description of the drawings: the project information in the scheme is project information of a science and technology project.
The beneficial effects of the first basic scheme are as follows: project information and enterprise information are acquired in the scheme, wherein the project information comprises: reporting condition information and success condition information, wherein although all item information is acquired, the information is not directly pushed or is completely presented through a webpage, so that an enterprise can screen the information by itself, but whether the enterprise meets reporting conditions or not is judged according to the reporting condition information and the enterprise information, so that the enterprise information meeting the reporting conditions is screened, and meanwhile, the enterprise is also screened to remove items which do not meet application conditions; then, for the enterprises meeting the reporting conditions, estimating probability values of successful reporting of the enterprises according to the success condition information and the enterprise information; and judging whether the probability value is greater than a first preset probability value, if so, pushing the project information to the enterprise, thereby helping the enterprise to obtain the project information which meets the application conditions and has certain success probability. The method includes recommending project information to the enterprise, timely reminding the enterprise that the projects can be declared at present, and simultaneously reminding the recommended projects to the enterprise that the projects can be declared, wherein the recommended projects are suitable projects with certain success probability, so that the enterprise selects the projects from the pushed project information to declare, the success probability of the projects is far greater than the success probability of blindly selecting the projects from all the projects to declare, time resources and human resources spent in searching the reportable projects are saved, the situations that the declared projects are not known, the projects meeting declaration conditions are not reported, and the projects with low declaration achievement reporting probability are effectively avoided, the enterprise is helped to enjoy support of countries and places under the condition, and the declaration of the projects with low success rate and the human resources and the time resources consumed by the projects with low success rate are reduced.
In conclusion, the scheme can help enterprises with reporting conditions to perform appropriate project reporting so as to improve the probability of successful reporting and reduce resource waste.
Further, the information acquiring step includes:
s101, collecting project information and enterprise information;
and S102, extracting declaration condition information and success condition information in the project information by adopting an artificial intelligence technology.
Has the beneficial effects that: project information typically contains a lot of content, such as: the targets, purposes and the like of the projects do not need information used in the process of auditing the projects, so that the reporting condition information and the success condition information in the project information are extracted by adopting an artificial intelligence technology, invalid information can be reduced, and effective information can be accurately extracted.
Further, the reporting judgment step:
s301, extracting related declaration information with matched characteristics in the enterprise information according to the declaration condition information;
s302, judging whether all the declaration condition information is extracted to obtain related declaration information, and if so, executing S303; if not, executing S306;
s303, judging whether the related declaration information accords with the declaration condition information, if so, executing S304; if not, executing S305;
s304, judging that the enterprise accords with the reporting condition, and executing a success rate estimation step;
s305, judging that the enterprise does not conform to the declaration condition;
and S306, acquiring declaration condition information of which the related declaration information is not extracted, pushing the declaration condition information to the enterprise, and executing the S301 again after the enterprise performs information supplementation.
Has the advantages that: in the reporting judgment step, firstly, according to reporting condition information, extracting relevant reporting information matched with features in the enterprise information, for example: if the declaration condition information is that the enterprise registered fund is not less than 10 ten thousand, extracting enterprise registered fund information in the enterprise information as related declaration information with matched features, and after extracting the related declaration information, not directly judging whether the related declaration information accords with the declaration condition information, but firstly judging whether all the declaration condition information is extracted to obtain the related declaration information, because the obtained enterprise information possibly has incomplete and incomplete problems or the enterprise does not have the declaration condition at all, firstly judging whether all the declaration condition information is extracted to obtain the related declaration information, if not, pushing the declaration condition information of the related declaration information without matched features to the enterprise, and if not, the enterprise sees the declaration condition information, can know whether the enterprise has the declaration condition and whether the enterprise accords with the condition, and if so, the enterprise can perform information supplementation, and then executing S301 again; if the enterprise does not have the declaration condition or the self condition is not met, the information is not supplemented, so that subsequent judgment is not needed, a large amount of computing resources are solved, all declaration condition information can be guaranteed to be extracted to relevant declaration information with matched characteristics, and the omission of the judgment of the subsequent declaration condition information is prevented.
Further, the S305 further includes: and executing S307;
s307, acquiring related declaration information which does not accord with declaration conditions;
and S308, performing improved analysis according to the related declaration information which does not accord with the declaration conditions and the corresponding declaration condition information, and pushing an improved analysis result to the enterprise.
Has the advantages that: although the enterprise is judged to be not in line with the declaration conditions, the enterprise has all declaration conditions but only the conditions are not in line, so that the related declaration information which is not in line with the declaration conditions is obtained, improvement analysis is carried out according to the related declaration information which is not in line with the declaration conditions and the corresponding declaration condition information, and the improvement analysis result is pushed to the enterprise to help the enterprise to adjust and upgrade the enterprise.
Further, the method also comprises the following steps: information judgment;
the information judging step includes:
s201, judging whether the acquired project information comprises declaration condition information and success condition information, if so, executing S202; if not, executing S206;
s202, judging whether missing information/fuzzy information exists in the declaration condition information or not, if so, executing S203; if not, executing S204;
s203, acquiring historical declaration condition information corresponding to the missing information/fuzzy information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of an administrative unit, supplementing the missing information/fuzzy information according to the historical declaration condition information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of the administrative unit, and executing S204;
s204, judging whether missing information/fuzzy information exists in the success condition information, if so, executing S205; if not, executing a reporting judgment step;
s205, acquiring historical success condition information corresponding to the missing information/fuzzy information or success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit, and supplementing the missing information/fuzzy information according to the historical success condition information or the success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit;
and S206, prompting that the project information is missing.
Has the advantages that: the acquired project information may have missing information/fuzzy information, or the reporting condition information and the success condition information extracted from the project information are not successfully extracted, or the missing information/fuzzy information exists, so the scheme further comprises an information judgment step of judging whether the reporting condition information and the success condition information are acquired or not, then judging whether the missing information/fuzzy information exists in the reporting condition information and the success condition information one by one, and if the missing information/fuzzy information exists, supplementing the reporting condition information and the success condition information corresponding to the missing information/fuzzy information in the same project of the same level of the historical information or the administrative unit, thereby supplementing the missing or fuzzy information to the maximum extent and the maximum similarity, not influencing the subsequent steps, and ensuring that the scheme can be completely carried out.
Further, the success condition information includes: necessary success condition information and score success condition information;
the necessary success condition information is success condition information which must be met before the project can be successfully declared;
and the score success condition information is success condition information for scoring the enterprise information with matched characteristics according to a preset scoring rule in the project.
Has the beneficial effects that: the conditions successfully declared in the existing project are generally divided into conditions which need to be met and conditions which are converted into corresponding scores, so that the success condition information acquired in the scheme comprises necessary success condition information and score success condition information which respectively correspond to the conditions which need to be met and the conditions which are converted into corresponding scores, and the completeness and comprehensiveness of the acquisition of the success condition information are guaranteed.
Further, the success rate estimating step includes:
s401, extracting relevant necessary success condition information matched with the characteristics in the enterprise information according to the necessary success condition information;
s402, judging whether all necessary success condition information is extracted to obtain relevant necessary success condition information, if so, executing S403; if not, executing S4011;
s403, judging whether the relevant necessary success condition information of the feature matching meets the necessary success condition information or not, if so, executing S404; if not, executing S4010;
s404, extracting relevant score success condition information of feature matching in the enterprise information according to the score success condition information;
s405, scoring the relevant score success condition information according to a preset scoring rule of each item of score success condition information in the project;
s406, calculating a total enterprise score according to the scoring result of each item of relevant score success condition information;
s407, judging whether the enterprise total score is larger than or equal to a preset total score, if so, executing S408; if not, executing S409;
s408, determining the probability value successfully declared by the enterprise as a preset highest probability value, and executing a probability value judgment step;
s409, mapping the total enterprise score to an interval of a preset lowest probability value and a preset highest probability value, obtaining a probability value successfully declared by the enterprise, and executing a probability value judgment step;
s4010, determining the probability value successfully declared by the enterprise as a preset lowest probability value, and executing a probability value judgment step;
s4011, obtaining necessary success condition information of which relevant necessary success condition information is not extracted, pushing the necessary success condition information to enterprises, and executing S401 again after the enterprises supplement the information.
Has the advantages that: for enterprises with inconsistent necessary success condition information, the probability of successful declaration is the preset lowest probability value, and the probability of successful application is almost 0, so that the enterprises do not need to be scored, and the operation processing space is saved; for enterprises meeting the necessary success condition information, the related score success condition information is scored according to a preset scoring rule of each item of score success condition information in the project, the total score of the enterprises is calculated according to the scoring result, the probability value of successful declaration of the enterprises with the total score being more than or equal to the preset total score is a preset highest probability value, the probability of successful application is almost 100%, for the enterprises with the total score being less than the preset total score, the total score of the enterprises is mapped into an interval of the preset lowest probability value and the preset highest probability value, the probability value of successful declaration of the enterprises is obtained, and the probability value is equivalent to the ranking, so that the enterprises can estimate whether the enterprises can successfully apply themselves.
Further, the method also comprises the following steps: adjusting and recommending;
the probability value judging step comprises the following steps:
s501, judging whether the probability value is larger than a first preset probability value or not, and if so, executing a pushing step; if not, executing S502;
s502, judging whether the probability value is larger than a second preset probability value or not, if so, executing an adjustment recommending step; if not, executing S503;
and S503, finishing matching.
The adjusting and recommending step comprises the following steps:
s701, obtaining adjustment information, wherein the adjustment information comprises: relevant score success condition information and score success condition information, wherein the scoring result of the relevant score success condition information is lower than the preset scoring score of the score success condition information;
s702, analyzing whether the enterprise has a promotion prospect in the score success condition information or not according to the adjustment information, if so, acquiring auxiliary mechanism information, and pushing the probability value successfully declared by the enterprise, the adjustment information, the auxiliary mechanism information and the project information to the enterprise.
Has the advantages that: the enterprise accords with the declaration condition information, but the success probability is lower than the first preset probability value, at this time, an enterprise condition which can be adjusted and improved may exist to increase the probability value of successful application, but if all the enterprises with the success probability lower than the first preset probability value are adjusted and recommended, the operation amount is huge, so that the enterprise above the limit is adjusted and recommended by taking the second preset probability value as the lowest limit, and the adjustment information is obtained, wherein the adjustment information comprises: relevant score success condition information and score success condition information, wherein the scoring result of the relevant score success condition information is lower than the preset scoring score of the score success condition information; and then analyzing whether the enterprise has a promotion prospect in the score success condition information or not according to the adjustment information, if so, acquiring auxiliary mechanism information, and pushing probability value successfully declared by the enterprise, the adjustment information, the auxiliary mechanism information and the project information to the enterprise, wherein the enterprise can self-adjust according to the adjustment information, and can select a more professional auxiliary mechanism to help self-adjust according to the auxiliary mechanism information so as to promote the probability of successful adjustment.
The invention also aims to provide a scientific and technological project accurate matching system based on artificial intelligence, which can help enterprises with declaration conditions to perform appropriate project declaration so as to improve the probability of successful declaration and reduce resource waste.
The invention provides a second basic scheme: the scientific and technological project accurate matching system based on artificial intelligence adopts the scientific and technological project accurate matching method based on artificial intelligence.
The second basic scheme has the beneficial effects that: the system can help enterprises with declaration conditions to perform proper project declaration so as to improve the probability of declaration success and reduce resource waste.
The invention further aims to provide a scientific and technological project accurate matching storage medium based on artificial intelligence, which can help enterprises with reporting conditions to perform appropriate project reporting so as to improve the reporting success probability and reduce resource waste.
The invention provides a third basic scheme: the technical project accurate matching storage medium based on artificial intelligence is characterized in that a computer program is stored on the storage medium, and when the computer program is executed by a processor, any one of the technical project accurate matching methods based on artificial intelligence is realized.
The third basic scheme has the beneficial effects that: the technical project accurate matching storage medium based on artificial intelligence is characterized in that a computer program is stored on the storage medium, and when the computer program is executed by a processor, the technical project accurate matching method based on artificial intelligence is realized, and an enterprise with reporting conditions can be helped to perform appropriate project reporting, so that the reporting success probability is improved, the resource waste is reduced, and the application of the technical project accurate matching method based on artificial intelligence is facilitated.
Drawings
FIG. 1 is a schematic flow chart illustrating an embodiment of a method for accurately matching science and technology projects based on artificial intelligence;
FIG. 2 is a schematic flow chart illustrating the information determination step in the embodiment of the method for accurately matching science and technology projects based on artificial intelligence;
FIG. 3 is a schematic flow chart illustrating a reporting judgment step in an embodiment of an artificial intelligence-based scientific and technological project precise matching method of the present invention;
FIG. 4 is a flowchart illustrating a success rate estimation step in an embodiment of an artificial intelligence-based scientific and technological project accurate matching method according to the present invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example one
The embodiment is basically as shown in the attached figure 1: an artificial intelligence based scientific and technological project accurate matching method comprises the following steps:
an information acquisition step: acquiring project information and enterprise information, wherein the project information comprises: reporting condition information and success condition information;
specifically, S101, collecting project information and enterprise information; in the embodiment, project information is collected in a project official website through a crawler, enterprise information is collected in the official website through the crawler, and enterprises can upload the enterprise information through a terminal;
s102, extracting declaration condition information and success condition information in the project information by adopting an artificial intelligence technology; in this embodiment, the existing artificial intelligent neural network is adopted to identify and extract text information of a successful declaration condition of a declaration condition, and then the declaration condition information and the successful condition information are output, which is not described in this embodiment again. Because project information typically contains much content, such as: the targets, purposes and the like of the projects do not need information used in the process of auditing the projects, so that the declared condition information and the success condition information in the project information are extracted by adopting a mature artificial intelligence technology in the prior art, invalid information can be reduced, and effective information can be accurately extracted.
An information judgment step: judging whether the acquired project information is complete, if so, executing a declaration judgment step; if not, after supplementing, executing a declaration judgment step; after all, the acquisition of the item information cannot guarantee the complete extraction of hundreds of percent, and if the item information is incomplete, the inaccuracy of the whole matching result may be caused, so that the information judgment step is set.
Specifically, as shown in fig. 2, S201 determines whether the acquired item information includes declaration condition information and success condition information, and if yes, executes S202; if not, executing S206; whether the acquired project information comprises declaration condition information and success condition information or not is judged, whether the declaration condition information and the success condition information are complete or not is guaranteed, the declaration condition information and the success condition information are acquired, and the situation that only one information is acquired, the other information is not acquired at all, or the situation that both data are not acquired is prevented.
S202, judging whether missing information/fuzzy information exists in the declaration condition information or not, if so, executing S203; if not, executing S204; in the scheme, the sum or the expression is given;
s203, acquiring historical declaration condition information corresponding to the missing information/fuzzy information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of an administrative unit, supplementing the missing information/fuzzy information according to the historical declaration condition information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of the administrative unit, and executing S204;
s204, judging whether missing information/fuzzy information exists in the success condition information, if so, executing S205; if not, executing a declaration judgment step, specifically executing S301;
s205, acquiring historical success condition information corresponding to the missing information/fuzzy information or success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit, and supplementing the missing information/fuzzy information according to the historical success condition information or the success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit;
and S206, prompting that the project information is missing. The missing information is missing information in the declaration condition information or the success condition information, for example: acquiring declaration condition information as the lowest value of the enterprise registered fund, and if the specific lowest value is not acquired, the specific lowest value is missing information; the lowest value of the acquired declaration condition information is 10-20 ten thousand yuan of enterprise registered fund, although the lowest value is acquired, the information is disputed, and the enterprise cannot determine a standard, so that the lowest value of 10-20 ten thousand yuan is fuzzy information; for the missing information/fuzzy information, the scheme is not directly ignored, because the neglect may affect the accuracy of the matching result, the scheme acquires the historical declaration condition information/success condition information corresponding to the missing information/fuzzy information or the declaration condition information/success condition information corresponding to the missing information/fuzzy information in the same item at the same level of the administrative unit, and supplements the same item, for example: the current actual information is the lowest value of the registered fund of the enterprise, the project information of the same project at the last time can be obtained, the specific information of the lowest value of the registered fund of the enterprise in the project information of the same project at the same level of the administrative unit can be extracted, or the specific information of the lowest value of the registered fund of the enterprise in the project information of the same project at the same level of the administrative unit can be obtained. In addition, some projects are executed according to administration units, each administration unit issues corresponding project information, and if missing information/fuzzy information exists in the project information issued by the current administration unit, reporting condition information/success condition information corresponding to the missing information/fuzzy information in the same project of the same level of the administration unit can be used.
Reporting and judging: judging whether the enterprise meets the reporting condition or not according to the reporting condition information and the enterprise information, and if so, executing a success rate estimation step;
specifically, as shown in fig. 3, S301, extracting relevant declaration information with matched features from the enterprise information according to declaration condition information; for example: if the declaration condition information is that the enterprise registered fund is not less than 10 ten thousand, extracting enterprise registered fund information in the enterprise information as related declaration information of feature matching;
s302, judging whether all the declaration condition information is extracted to obtain related declaration information, and if so, executing S303; if not, executing S306;
s303, judging whether the related declaration information accords with the declaration condition information, if so, executing S304; if not, executing S305;
s304, judging that the enterprise meets the reporting condition, and executing a success rate estimation step, specifically executing S401;
s305, judging that the enterprise does not conform to the declaration condition, and executing S307;
s306, obtaining the declaration condition information of unextracted related declaration information, pushing the declaration condition information to an enterprise, and executing the S301 again after the enterprise performs information supplementation;
s307, acquiring related declaration information which does not accord with declaration conditions;
and S308, performing improved analysis according to the related declaration information which does not conform to the declaration condition and the corresponding declaration condition information, and pushing an improved analysis result to the enterprise.
After the relevant declaration information is extracted in the above steps, whether the relevant declaration information meets the declaration condition information is not directly judged, but whether all the declaration condition information is extracted is firstly judged, because the obtained enterprise information may have incomplete and incomplete problems or the enterprise does not have the declaration condition at all, so that whether all the declaration condition information is extracted is firstly judged, if not, the declaration condition information of the relevant declaration information with matched characteristics is not extracted and is pushed to the enterprise, the enterprise sees the declaration condition information, can know whether the declaration condition is met, and if the declaration condition is met, the enterprise can perform information supplementation, and then S301 is executed again; if the enterprise does not have the declaration condition or the self condition is not met, the information is not supplemented, so that subsequent judgment is not needed, a large amount of computing resources are solved, all declaration condition information can be guaranteed to be extracted to relevant declaration information with matched characteristics, and the omission of the judgment of the subsequent declaration condition information is prevented. For some enterprises, although the enterprises are judged to be not in accordance with the declaration conditions, the enterprises have all declaration conditions but only the conditions are not in accordance, so that relevant declaration information which is not in accordance with the declaration conditions is obtained, the existing data analysis algorithm is adopted for improvement and analysis according to the relevant declaration information which is not in accordance with the declaration conditions and the corresponding declaration condition information, and the improvement and analysis results are pushed to the enterprises so as to help the enterprises to adjust and upgrade the enterprises, for example: the reporting condition information is as follows: and if the number of the enterprise employees is not less than 100, extracting the number of the enterprise employees 99 and the number of the enterprise employees not less than 100, analyzing to know that the number of the enterprise employees is less than the minimum number of the enterprise employees, specifically less than one, sending the analysis result to the enterprise, and completely recruiting one employee before declaration by the enterprise.
A success rate estimation step: estimating the probability value of successful declaration of the enterprise according to the success condition information and the enterprise information; the success condition information comprises: necessary success condition information and score success condition information; the necessary success condition information is success condition information which must be met to successfully declare the project; the score success condition information is success condition information for scoring the enterprise information with matched characteristics according to a preset scoring rule in the project; the conditions successfully declared in the existing project are generally divided into conditions which need to be met and conditions which are converted into corresponding scores, so that the success condition information acquired in the scheme comprises necessary success condition information and score success condition information which respectively correspond to the conditions which need to be met and the conditions which are converted into corresponding scores, and the completeness and comprehensiveness of the acquisition of the success condition information are guaranteed.
Specifically, as shown in fig. 4, S401, extracting relevant necessary success condition information of feature matching in the enterprise information according to the necessary success condition information; for example: the business information is a project released in the XX city, the necessary success condition information is that the business registration place is the XX city, and the registration place information of the business in the business information is extracted;
s402, judging whether all necessary success condition information is extracted to obtain related necessary success condition information, if so, executing S403; if not, executing S4011; whether all necessary success condition information is extracted to relevant necessary success condition information is judged firstly, and the condition that the relevant necessary success condition information of an enterprise does not accord with the necessary success condition information due to incomplete information extraction is prevented;
s403, judging whether the relevant necessary success condition information of the feature matching meets the necessary success condition information or not, if so, executing S404; if not, executing S4010; for example: the business information is an item released in the XX city, the necessary success condition information is the business registration place XX city, the registration place information of the business in the extracted business information is the AA city, and the relevant necessary success condition information does not accord with the necessary success condition information; if the information of the registration place of the enterprise in the extracted enterprise information is XX city, the relevant necessary success condition information accords with the necessary success condition information;
s404, extracting relevant score success condition information of feature matching in the enterprise information according to the score success condition information; for example: if the score success condition information is that the number of the high-value patents owned by the enterprise is not less than 5, extracting the number of the high-value patents of the enterprise from the enterprise information;
s405, scoring the relevant score success condition information according to a preset scoring rule of each item of score success condition information in the project; for example: the successful scoring condition information is that the number of the high-value patents owned by the enterprise is not less than 6, the score passing rule is preset, the number of the high-value patents owned by the enterprise meets the minimum requirement, the passing score is 60, 10 more high-value patents are obtained when each high-value patent is added, the full score is 100, and the number of the zero scores is obtained when the number of the high-value patents owned by the enterprise does not meet the minimum requirement; if the number of the high-value patents extracted from the enterprise information is 7, scoring 70 for the relevant scoring success condition information corresponding to the scoring success condition information;
s406, calculating a total enterprise score according to the scoring result of each item of relevant score success condition information; the total score of each item of relevant score success condition information is the same, so that the scoring results of the relevant score success condition information are enabled to be additive;
s407, judging whether the total score of the enterprise is greater than or equal to a preset total score, if so, executing S408; if not, executing S409;
s408, determining the probability value successfully declared by the enterprise as a preset highest probability value, and executing a probability value judgment step, specifically executing S501; in this embodiment, the highest probability value is 99%;
s409, mapping the enterprise total score to an interval of a preset lowest probability value and a preset highest probability value, obtaining a probability value successfully declared by the enterprise, executing a probability value judgment step, and specifically executing S501;
s4010, determining that the probability value successfully declared by the enterprise is a preset lowest probability value, executing a probability value judgment step, and specifically executing S501; in this embodiment, the lowest probability value is 0%; for enterprises with inconsistent necessary success condition information, the probability of successful declaration is the preset lowest probability value, and the probability of successful application is almost 0, so that the enterprises do not need to be scored, and the operation processing space is saved;
s4011, acquiring necessary success condition information of which relevant necessary success condition information is not extracted, pushing the necessary success condition information to enterprises, and executing S401 again after the enterprises supplement the information.
A probability value judgment step: judging whether the probability value is greater than a first preset probability value or not, if so, executing a pushing step;
specifically, S501, judging whether the probability value is larger than a first preset probability value, if so, executing a pushing step; if not, executing S502; in the embodiment, the first preset probability value is 60%, the success rate of the enterprise applying for the project is higher than 6, the success probability is high, and the enterprise can apply for the project;
s502, judging whether the probability value is larger than a second preset probability value, if so, executing an adjustment recommendation step, and specifically executing S701; if not, executing S503; in the embodiment, the second preset probability value is 40%, the success rate of the enterprise applying for the project is higher than 4, the success probability is low, and a strived space exists;
and S503, finishing matching.
A recommendation step: pushing project information to the enterprise; the embodiment also pushes the probability value to the enterprise together, and the probability value may be a terminal of the sending enterprise.
Adjusting and recommending: acquiring adjustment information, analyzing enterprise promotion prospects according to the adjustment information, and pushing the enterprise promotion prospects to the enterprise;
specifically, S701, obtaining adjustment information, where the adjustment information includes: relevant score success condition information and score success condition information, wherein the scoring result of the relevant score success condition information is lower than the preset scoring score of the score success condition information;
s702, analyzing whether the enterprise has a promotion prospect in the score success condition information or not according to the adjustment information, if so, acquiring auxiliary mechanism information, and pushing the probability value successfully declared by the enterprise, the adjustment information, the auxiliary mechanism information and the project information to the enterprise. For example: the probability value of successful application of the enterprise is 59%, score success condition information indicates that the enterprise has no less than 6 high-value patents, the enterprise has only 5 high-value patents, the lowest requirement is met, the score is 0, and the preset score of the score success condition information is 60, so that relevant score success condition information (the enterprise has 5 high-value patents) and score success condition information (the enterprise has no less than 6 high-value patents) are obtained and serve as adjustment information; according to the adjustment information, the existing data analysis technology is adopted to analyze whether the enterprise has a promotion prospect in the score success condition information, if the enterprise is engaged in a strategic emerging industry, and the previous applied patents and the generated products belong to the strategic emerging industry, the enterprise has the promotion prospect in the score success condition information, auxiliary mechanism information can be obtained, such as a patent agent structure capable of project declaration, and the probability value, the adjustment information, the auxiliary mechanism information and the project information which are successfully declared by the enterprise are pushed to the enterprise, so that the enterprise can self-adjust according to the adjustment information, and can select a more professional auxiliary mechanism to help self-adjust according to the auxiliary mechanism information, so as to promote the probability of successful adjustment.
In addition, the enterprise reporting the project success can upload the information such as experience and materials of the enterprise success to a designated platform, and other enterprises can inquire or download the information in a payment sharing mode so as to help the enterprise to learn.
According to the scheme, the project information and the enterprise information are obtained, although all the project information is obtained, the project information is not directly pushed or is completely presented through a webpage, and an enterprise can screen the project information by itself, but whether the enterprise meets the declaration condition or not is judged according to the declaration condition information and the enterprise information, the enterprise information meeting the declaration condition is screened, and meanwhile, the enterprise is also screened to remove the projects which do not meet the application condition; and calculating the probability value of successful declaration for the enterprises meeting the declaration condition, thereby helping the enterprises to obtain the project information meeting the application condition and having a certain success probability. The method includes recommending project information to the enterprise, timely reminding the enterprise that the projects can be declared at present, and simultaneously reminding the recommended projects to the enterprise that the projects can be declared, wherein the recommended projects are suitable projects with certain success probability, so that the enterprise selects the projects from the pushed project information to declare, the success probability of the projects is far greater than the success probability of blindly selecting the projects from all the projects to declare, time resources and human resources spent in searching the reportable projects are saved, the situations that the declared projects are not known, the projects meeting declaration conditions are not reported, and the projects with low declaration achievement reporting probability are effectively avoided, the enterprise is helped to enjoy support of countries and places under the condition, and the declaration of the projects with low success rate and the human resources and the time resources consumed by the projects with low success rate are reduced.
In conclusion, the scheme can help enterprises with reporting conditions to perform appropriate project reporting so as to improve the probability of successful reporting and reduce resource waste.
The embodiment also provides a scientific and technological project accurate matching system based on artificial intelligence, and the scientific and technological project accurate matching method based on artificial intelligence is used.
The above-mentioned precision matching method for science and technology projects based on artificial intelligence can be stored in a readable storage medium if it is implemented in the form of software functional unit and sold or used as an independent product. Based on such understanding, all or part of the flow in the method of the above embodiments may be realized by a computer program, which may be stored in a readable storage medium and used for instructing relevant hardware, and when the computer program is executed by a processor, the steps of the above method embodiments may be realized. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc.
Example two
This embodiment is substantially the same as the above embodiment except that: the probability value judging step comprises the following steps: judging whether the probability value is greater than a first preset probability value or not, if so, executing a pushing step; if not, executing an adjustment recommendation step; thereby helping more enterprises to adjust and promote themselves as much as possible.
EXAMPLE III
This embodiment is substantially the same as the first embodiment except that: the S306 further includes:
how business information inconsistencies or deletions are handled
Acquiring historical data of a project corresponding to enterprise declaration according to the declaration condition information of the unextracted related declaration information;
extracting historical enterprise information from historical data;
supplementing information which does not exist in the existing enterprise information according to the historical enterprise information;
and comparing the time of the information existing in the existing enterprise information, if the time of the information corresponding to the historical enterprise information is updated, updating the information existing in the existing enterprise information into the information corresponding to the historical enterprise information, and then executing the step S301 again, or pushing the information to the enterprise, and executing the step S301 again after the enterprise supplements the information. Specifically, for example, in the existing enterprise information, the data of 2018 is that the information of the number of enterprise personnel is 100, and the data of 2020 is that the information of the number of enterprise personnel is also included in the extracted historical enterprise information, so that the information of the number of enterprise personnel in the existing enterprise information can be updated to 120, and the missing enterprise information can be supplemented in the historical data, and some enterprise information can be automatically updated.
Example four
This embodiment is substantially the same as the first embodiment, except that: the acquiring of the auxiliary institution information further includes: according to the score success condition information with the foreground, acquiring auxiliary mechanism information with the corresponding processed condition; for example: the probability value of successful application of an enterprise is 59%, score success condition information indicates that the enterprise has no less than 6 high-value patents, the enterprise has only 5 high-value patents, the lowest requirement is met, the score is 0, and the preset score of the score success condition information is 60, so that relevant score success condition information (the enterprise has 5 high-value patents) and score success condition information (the enterprise has no less than 6 high-value patents) are obtained and serve as adjustment information; and analyzing whether the enterprise has a promotion prospect in the score success condition information or not by adopting the existing data analysis technology according to the adjustment information, if the enterprise is engaged in a strategic emerging industry, and the previously applied patents and the generated products belong to the strategic emerging industry, the enterprise has the promotion prospect in the score success condition information, and can obtain auxiliary mechanism information, if the enterprise is treated for not less than a preset number of times, mechanisms for increasing the number of high-value patents owned by the enterprise are added.
The pushing step further comprises: and acquiring auxiliary organization information with auxiliary reporting of the project success data, and pushing the auxiliary organization information and the project information to the enterprise.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several variations and modifications can be made, which should also be considered as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the utility of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The scientific and technological project accurate matching method based on artificial intelligence is characterized by comprising the following steps: the method comprises the following steps:
an information acquisition step: acquiring project information and enterprise information, wherein the project information comprises: reporting condition information and success condition information;
reporting and judging: judging whether the enterprise accords with the reporting condition or not according to the reporting condition information and the enterprise information, and if so, executing a success rate estimation step;
a success rate estimation step: estimating the probability value of successful declaration of the enterprise according to the success condition information and the enterprise information;
a probability value judgment step: judging whether the probability value is greater than a first preset probability value or not, if so, executing a pushing step;
a recommendation step: and pushing the project information to the enterprise.
2. The method for accurately matching science and technology projects based on artificial intelligence according to claim 1, wherein the method comprises the following steps: the information acquisition step includes:
s101, collecting project information and enterprise information;
and S102, extracting declaration condition information and success condition information in the project information by adopting an artificial intelligence technology.
3. The method for accurately matching science and technology projects based on artificial intelligence according to claim 1, wherein the method comprises the following steps: the reporting judgment step comprises:
s301, extracting related declaration information with matched characteristics in the enterprise information according to the declaration condition information;
s302, judging whether all the declaration condition information is extracted to obtain related declaration information, and if so, executing S303; if not, executing S306;
s303, judging whether the related declaration information accords with the declaration condition information, if so, executing S304; if not, executing S305;
s304, judging that the enterprise meets the reporting condition, and executing a success rate estimation step;
s305, judging that the enterprise does not accord with the declaration condition;
s306, obtaining the declaration condition information of the unextracted related declaration information, pushing the declaration condition information to the enterprise, and executing the S301 again after the enterprise performs information supplementation.
4. The method for accurately matching science and technology projects based on artificial intelligence according to claim 3, wherein the method comprises the following steps: the S305 further includes: and executes S307;
s307, acquiring related declaration information which does not accord with declaration conditions;
and S308, performing improved analysis according to the related declaration information which does not conform to the declaration condition and the corresponding declaration condition information, and pushing an improved analysis result to the enterprise.
5. The method for accurately matching science and technology projects based on artificial intelligence according to claim 1, wherein the method comprises the following steps: further comprising: information judgment;
the information judging step includes:
s201, judging whether the acquired project information comprises declaration condition information and success condition information, if so, executing S202; if not, executing S206;
s202, judging whether missing information/fuzzy information exists in the declaration condition information or not, if so, executing S203; if not, executing S204;
s203, acquiring historical declaration condition information corresponding to the missing information/fuzzy information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of an administrative unit, supplementing the missing information/fuzzy information according to the historical declaration condition information or declaration condition information corresponding to the missing information/fuzzy information in the same project of the same level of the administrative unit, and executing S204;
s204, judging whether missing information/fuzzy information exists in the success condition information, if so, executing S205; if not, executing a reporting judgment step;
s205, acquiring historical success condition information corresponding to the missing information/fuzzy information or success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit, and supplementing the missing information/fuzzy information according to the historical success condition information or the success condition information corresponding to the missing information/fuzzy information in the same item of the same level of the administrative unit;
and S206, prompting that the project information is missing.
6. The method for accurately matching science and technology projects based on artificial intelligence according to claim 1, wherein the method comprises the following steps: the success condition information includes: necessary success condition information and score success condition information;
the necessary success condition information is success condition information which must be met before the project can be successfully declared;
and the score success condition information is success condition information for scoring the enterprise information matched with the characteristics according to a preset scoring rule in the project.
7. The method for accurately matching science and technology projects based on artificial intelligence according to claim 6, wherein the method comprises the following steps: the success rate estimating step includes:
s401, extracting relevant necessary success condition information matched with the characteristics in the enterprise information according to the necessary success condition information;
s402, judging whether all necessary success condition information is extracted to obtain relevant necessary success condition information, if so, executing S403; if not, executing S4011;
s403, judging whether the relevant necessary success condition information of the feature matching meets the necessary success condition information or not, if so, executing S404; if not, executing S4010;
s404, extracting relevant score success condition information of feature matching in the enterprise information according to the score success condition information;
s405, scoring the relevant score success condition information according to a preset scoring rule of each item of score success condition information in the project;
s406, calculating a total enterprise score according to the scoring result of each item of relevant score success condition information;
s407, judging whether the total score of the enterprise is greater than or equal to a preset total score, if so, executing S408; if not, executing S409;
s408, determining the probability value successfully declared by the enterprise as a preset highest probability value, and executing a probability value judgment step;
s409, mapping the total score of the enterprise to a preset lowest probability value and a preset highest probability value interval, obtaining a probability value successfully declared by the enterprise, and executing a probability value judgment step;
s4010, determining the probability value successfully declared by the enterprise as a preset lowest probability value, and executing a probability value judgment step;
s4011, obtaining necessary success condition information of which relevant necessary success condition information is not extracted, pushing the necessary success condition information to enterprises, and executing S401 again after the enterprises supplement the information.
8. The method for accurately matching science and technology projects based on artificial intelligence according to claim 7, wherein the method comprises the following steps: further comprising: adjusting and recommending;
the probability value judging step comprises the following steps:
s501, judging whether the probability value is larger than a first preset probability value or not, and if so, executing a pushing step; if not, executing S502;
s502, judging whether the probability value is larger than a second preset probability value or not, and if so, executing an adjustment recommendation step; if not, executing S503;
and S503, finishing matching.
The step of adjusting recommendation comprises:
s701, obtaining adjustment information, wherein the adjustment information comprises: relevant score success condition information and score success condition information, wherein the scoring result of the relevant score success condition information is lower than the preset scoring score of the score success condition information;
s702, analyzing whether the enterprise has a promotion prospect in the score success condition information or not according to the adjustment information, if so, acquiring auxiliary mechanism information, and pushing the probability value successfully declared by the enterprise, the adjustment information, the auxiliary mechanism information and the project information to the enterprise.
9. Accurate matching system of science and technology project based on artificial intelligence, its characterized in that: the method for accurately matching the science and technology project based on artificial intelligence according to any one of claims 1 to 8.
10. Scientific and technological project accurate matching storage medium based on artificial intelligence, the storage medium stores computer program, its characterized in that: the computer program, when executed by a processor, implements the artificial intelligence based technology project precision matching method of any one of claims 1-8.
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