A teacher resource acquisition method, system and terminal device

Abstract

The embodiment of the present application provides a teacher resource acquisition method, system and terminal device, the method comprising: obtaining the R&D needs of the enterprise and obtaining the demand synonym tree of each demand keyword in the R&D needs; extracting different resource information of each teacher to classify them into different resource attributes and generate corresponding resource synonym trees; calculating the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher; calculating the total matching degree of the corresponding teacher based on the preset weight and matching degree of each resource attribute of the corresponding teacher; pushing the preset number of teacher information with the highest matching degree to the enterprise. This method can realize the rapid extraction of suitable teacher resources from the huge teaching staff of colleges and universities and push them to enterprises. Compared with manual resource screening, it can greatly improve the efficiency of teacher resource search.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a teacher resource acquisition method, system and terminal device. Background Art

[0002] Some companies focus on production and have good implementation capabilities, but lack R&D strength. Therefore, they often encounter various technical problems that need to be solved in production, such as developing new products and expanding new businesses. At this time, if you can use the cutting-edge research results of university teachers to guide or cooperate in R&D, you can greatly speed up the solution of the above technical problems.

[0003] Since colleges and universities have abundant teacher resources, according to statistics in 2020, there are 1.602 million full-time teachers in colleges and universities across the country. For enterprises, it is not easy to obtain teacher resources in a narrow production field from this massive amount of teacher resources. Summary of the invention

[0004] In view of this, an embodiment of the present application provides a teacher resource acquisition method, system and terminal device.

[0005] In a first aspect, an embodiment of the present application provides a method for acquiring teacher resources, comprising:

[0006] Acquire the R&D needs of the enterprise, and generate a demand synonym tree for each demand keyword in the R&D needs;

[0007] Classify each teacher's information into different resource attributes, and generate a resource synonym tree for each word in each resource attribute;

[0008] Calculate the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher;

[0009] Calculate the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree;

[0010] The total matching degrees of all teachers are sorted, and information of a preset number of teachers with the highest matching degrees is pushed to the enterprise.

[0011] In some embodiments, the different resource attributes include projects, papers and research areas of each teacher; each resource attribute is described by a corresponding keyword list and each word in the keyword list has a respective resource synonym tree;

[0012] The calculating the matching score of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and the resource synonym tree of each resource attribute of the corresponding teacher comprises:

[0013] Searching in the resource synonym tree of the keyword list of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword;

[0014] If the word is found in the resource synonym tree, it is determined that the word matches the current demand keyword, and the distance between the word in the resource synonym tree and the word in the demand synonym tree is calculated;

[0015] Then, the words in the demand synonym tree according to the current demand keyword are returned, and a search step is performed in the resource synonym tree of the keyword list of the current resource attribute until all demand keywords are traversed to obtain a number of distances;

[0016] The matching degree between the research and development demand and the current resource attribute of the current teacher is calculated according to the several distances.

[0017] In some embodiments, the different resource attributes include projects, papers and research fields of each teacher; each resource attribute is described by a corresponding keyword list, and the keyword list of the current resource attribute includes at least one keyword sublist, and each word in the keyword sublist has a respective resource synonym tree;

[0018] Searching in the resource synonym tree of the current keyword sublist of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword;

[0019] If it is found in the resource synonym tree, it is determined that the current demand keyword is matched, and the distance between the words in the resource synonym tree and the words in the demand synonym tree of the found current keyword sublist is calculated;

[0020] Then, the words in the demand synonym tree according to the current demand keyword are returned, and a search step is performed in the resource synonym tree of the current keyword sublist of the current resource attribute until all demand keywords are traversed to obtain a number of distances;

[0021] Calculating the total distance between the R&D demand and the current keyword sublist according to the first preset formula based on the plurality of distances, and then calculating the total distance between the R&D demand and the next keyword sublist until all keyword sublists of the current resource attribute are traversed;

[0022] According to the total distance between the research and development demand and each keyword sublist of the current resource attribute, the matching degree between the research and development demand and the current resource attribute of the current teacher is calculated according to the second preset formula.

[0023] In some embodiments, obtaining the distance between the words in the resource synonym tree and the words in the requirement synonym tree includes:

[0024] The position levels of the words in the resource synonym tree and the words in the demand synonym tree in their respective synonym trees are determined respectively, and the distance between the two words is calculated according to the following formula:

[0025] S ab =k (Ha+Hb-2) ;

[0026] Among them, S ab It represents the distance between the two words corresponding to the current demand keyword, k is a preset value, Ha and Hb represent the position levels of the two words in their respective synonym trees.

[0027] In some embodiments, the first preset formula is as follows:

[0028]

[0029] Where Si represents the total distance between the i-th keyword sublist according to the R&D demand and the current resource attribute, S j represents the distance corresponding to the jth demand keyword, where m is the number of matches between the demand synonym tree and the resource synonym tree of the current keyword sublist.

[0030] In some embodiments, the second preset formula is as follows:

[0031]

[0032] Among them, X represents the matching degree between the research and development demand and the current resource attribute of the current teacher, and n represents the total number of the demand keywords.

[0033] In some embodiments, the calculation formula of the total matching degree of the corresponding teacher is as follows:

[0034] Y=Wp*Xp+Wt*Xt+Wf*Xf;

[0035] In the formula, Y represents the overall matching degree of the teacher, Xp, Xt and Xf are the matching degrees of the project, the paper and the research field respectively, Wp, Wt and Wf are the preset weights of the project, the paper and the research field respectively, and the ratio of Wp to Wt and the ratio of Wt to ​​Wf are not less than the preset multiples.

[0036] In a second aspect, an embodiment of the present application provides a teacher resource acquisition system, including:

[0037] A demand synonym tree acquisition module is used to acquire the R&D demand of the enterprise and generate a demand synonym tree for each demand keyword in the R&D demand;

[0038] A resource synonym tree acquisition module is used to classify each teacher's information into different resource attributes and generate a resource synonym tree for each word in each resource attribute;

[0039] A synonym tree matching module, used for calculating the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher;

[0040] A total matching degree calculation module, used for calculating the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree;

[0041] The teacher resource acquisition module is used to sort the total matching degrees of all teachers and push the information of a preset number of teachers with the highest matching degrees to the enterprise.

[0042] In a third aspect, an embodiment of the present application provides a terminal device, comprising a processor and a memory, wherein the memory stores a computer program, and the processor is used to execute the computer program to implement the above-mentioned teacher resource acquisition method.

[0043] In a fourth aspect, an embodiment of the present application provides a readable storage medium storing a computer program, which, when executed on a processor, implements the above-mentioned teacher resource acquisition method.

[0044] The embodiments of the present application have the following beneficial effects:

[0045] The teacher resource acquisition method of the embodiment of the present application obtains the R&D needs of the enterprise and generates a demand synonym tree for each demand keyword in the R&D needs, and extracts each teacher information to generate a corresponding resource synonym tree; then, according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher, the matching degree of each resource attribute of the corresponding teacher is calculated; based on the preset weight and matching degree of each resource attribute of the corresponding teacher, the total matching degree of the corresponding teacher is calculated; and the preset number of teacher information with the highest matching degree is pushed to the enterprise. This method uses multi-level synonym trees and weight allocation to match teacher resources with R&D needs, which can quickly extract suitable teacher resources from the huge teaching staff of colleges and universities and push them to enterprises. Compared with manual resource screening, it can greatly improve the efficiency of teacher resource search. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0047] Figure 1 A first flow chart of the teacher resource acquisition method according to an embodiment of the present application is shown;

[0048] Figure 2 A schematic diagram of a demand synonym tree according to an embodiment of the present application is shown;

[0049] Figure 3 A second flow chart of the teacher resource acquisition method according to an embodiment of the present application is shown;

[0050] Figure 4 A third flow chart of the teacher resource acquisition method of an embodiment of the present application is shown;

[0051] Figure 5 A structural diagram of a teacher resource acquisition system according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0052] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0053] The components of the embodiments of the present application generally described and shown in the drawings herein may be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0054] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing items or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations of the foregoing items.

[0055] Furthermore, the terms “first”, “second”, “third”, etc. are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0056] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as those generally understood by those skilled in the art to which the various embodiments of the present application belong. The terms (such as those defined in generally used dictionaries) will be interpreted as having the same meanings as the contextual meanings in the relevant technical field and will not be interpreted as having idealized meanings or overly formal meanings unless clearly defined in the various embodiments of the present application.

[0057] Example 1

[0058] Figure 1 The first flow chart of the teacher resource acquisition method of the embodiment of the present application is shown. Exemplarily, the teacher resource acquisition method includes:

[0059] Step S100, obtaining the R&D requirements of the enterprise, and generating a requirement synonym tree for each requirement keyword in the R&D requirements.

[0060] Generally speaking, enterprises often encounter various technical problems that need to be solved during production, such as the research and development of new products, solving technical troubleshooting on actual production lines, performance optimization, etc. The solution to these technical problems is the corresponding R&D needs of the enterprise.

[0061] In one implementation, for the R&D needs of an enterprise, corresponding scientific and technological terms can be extracted from the actual needs and stored in the form of a list or array, such as list1{keyword1, keyword2, ...}, so that the computer can recognize it. Then, each demand keyword in the acquired R&D needs is expanded in synonyms to construct a corresponding synonym tree.

[0062] For example, if the company's demand is to optimize the performance of a fluff pulp crusher, then the demand is input into the corresponding scientific and technological terminology database for scientific and technological term extraction. At this time, the specific R&D demand can be extracted as: list1{'fluff pulp', 'crusher'}, etc. Then, taking 'fluff pulp' as an example, synonym expansion is performed, such as Figure 2 As shown, a requirement synonym tree for 'fluff pulp' may include {'wood pulp', 'paper pulp', 'hygroscopic material', 'water-absorbing medium'}, etc.

[0063] It is understandable that when expanding, it can be expanded downward by 1 to 2 levels, which can be determined according to the actual research and development demand field, etc. Among them, the above-mentioned scientific and technological terms can be some databases covering standardized terms in different technical fields published by authoritative institutions or platforms. The selection of specific databases is not limited here, and users can choose according to actual conditions.

[0064] Step S200: classify each teacher information into different resource attributes, and generate a resource synonym tree for each word in each resource attribute.

[0065] For the information of college teachers, for example, it can be automatically captured from the corresponding web pages through tools such as crawlers, or it can be pre-entered manually, etc., which is not limited here. Specifically, using the name of each teacher as a label, collect relevant data such as the projects, papers, patents, teaching subjects, research fields and titles that the teacher participates in, and then classify this information according to different resource attributes. Then, similarly, the above-mentioned synonym expansion method is used to obtain the resource synonym tree of each word.

[0066] In an optional solution, several different resource attributes can be pre-set according to the degree of help to the enterprise R&D, for example, including but not limited to papers, research fields, projects, etc. For resource information related to these three categories, the specific content of each type of resource attribute can be obtained through word segmentation, keyword extraction of scientific and technological terms, etc., and stored in the form of corresponding arrays or lists.

[0067] Furthermore, if a teacher participates in many projects or publishes many papers, different projects and papers can be further distinguished and stored in the form of sub-arrays or sub-lists. It should be understood that in actual operation, if there is other information such as patents and teaching subjects, it can be further classified into these four items. For example, the name of the patent can be put into the project array, and the teaching subject can be classified into the research field array.

[0068] For example, a teacher has two projects, namely: a. a natural science foundation project: "analog circuit fault diagnosis research"; b. a project topic "application of support vector machine in analog circuit faults". Then the resource attribute projects[] about the teacher's project may include two sub-projects {project[0], project[1]}. Furthermore, each project contains its own keywords. For example, project[1] can be described as {'analog circuit', 'fault diagnosis', 'support vector machine'}. The above list of scientific and technological terms can be obtained through word segmentation and keyword extraction based on the scientific and technological term corpus.

[0069] It is understandable that for such a huge amount of teacher resources, automatic acquisition through the use of computers with the help of corresponding data processing technologies such as word segmentation and keyword extraction can not only greatly reduce the time cost of manual extraction, but also reduce the error rate and omission of some data.

[0070] Step S300, calculating the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher.

[0071] This embodiment matches all resource synonym trees according to the words in the requirement synonym tree of each requirement keyword in the R&D requirement, so as to calculate the matching score of each resource attribute of each teacher. Taking the above three resource attributes as an example, when there is only one keyword list for each resource attribute, each word in the keyword list has its own resource synonym tree. In one embodiment, Figure 3 As shown, the above step S300 includes sub-steps S301 to S304:

[0072] Sub-step S301, searching in the resource synonym tree of the keyword list of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword.

[0073] For example, for each requirement keyword in the R&D requirement list1, it can be matched in the keyword list of the teacher's project resource attribute projects[]. Specifically, the resource synonym tree of each word in the keyword list can be searched in turn to see whether there is a word in the requirement synonym tree for each requirement keyword. If two identical words exist, it indicates that the corresponding requirement keyword is matched.

[0074] Sub-step S302, if the word is found in the resource synonym tree, it is determined that the current demand keyword is matched, and the distance between the word found in the resource synonym tree and the word in the demand synonym tree is calculated.

[0075] For a certain demand keyword, if a word in a demand synonym tree is found in a resource synonym tree, the hierarchical positions of the two words in their respective synonym trees are recorded, that is, the hierarchical positions of the two words in the trees, and then the distance between the two words is calculated based on the hierarchical positions. For example, in one embodiment, the distance between the two words is calculated according to the following formula:

[0076] S ab =k (Ha+Hb-2) ;

[0077] Among them, S ab It represents the distance between a word in the demand synonym tree corresponding to a demand keyword and the same word found in the resource synonym tree. k is a preset value. Ha and Hb represent the position levels of the two words in their respective synonym trees.

[0078] Optionally, if the synonym is not found in the current resource synonym tree, the search continues in the next resource synonym tree, and if it is found, the distance is also calculated.

[0079] Sub-step S303, then returns to sub-step S301, until all the demand keywords are traversed and a number of distances are obtained.

[0080] It can be understood that for each demand keyword, the above sub-steps S301 to S302 are processed in the same manner until all demand keywords are searched, at which time the distances corresponding to some or all of the demand keywords are obtained.

[0081] Sub-step S304, calculating the matching degree between the R&D demand and the current resource attribute of the current teacher according to the plurality of distances.

[0082] After obtaining the word matching between the R&D demand and the current resource attribute, for example, the matching degree of the current resource attribute can be calculated according to the following formula:

[0083]

[0084] Among them, S represents the total distance between the keyword list based on the R&D demand and the current resource attributes, S j represents the distance corresponding to the jth requirement keyword that is successfully matched, and m is the number of matches between the requirement synonym tree and the resource synonym tree of the keyword list of the current resource attribute.

[0085] It can be understood that for each type of resource attribute mentioned above, the matching degree between it and the same research and development demand can be calculated according to the above sub-steps, and then the matching degree between each type of resource attribute of the teacher and the research and development demand can be obtained.

[0086] Considering that in actual situations, each teacher often participates in more than one project or publishes more than one paper, the keyword list of each resource attribute includes multiple keyword sublists. After synonym expansion, each word in each keyword sublist can be obtained. Figure 4 As shown, the above step S300 includes sub-steps S311 to S315:

[0087] Sub-step S311, searching in the resource synonym tree of the current keyword sub-list of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword.

[0088] Similar to the above sub-step S301, for a certain demand keyword keyword, you can search in the resource synonym tree of each keyword sub-list in turn. If the word in the demand synonym tree of the demand keyword keyword is found in the current resource synonym tree, it is considered a match, and the distance between the two words is calculated. Otherwise, continue to search in the next resource synonym tree.

[0089] Sub-step S312, if the word is found in the resource synonym tree, it is determined that the current demand keyword is matched, and the distance between the word in the resource synonym tree and the word in the demand synonym tree of the current keyword sublist is calculated.

[0090] For the specific calculation of the distance, please refer to the above sub-step S302, which will not be repeated here.

[0091] Sub-step S313, then returns to step S311, until all the demand keywords are traversed and a number of distances are obtained.

[0092] It can be understood that after traversing all the demand keywords, the corresponding distance can be calculated for the successfully matched demand keywords. It is worth noting that this embodiment will first calculate the matching degree between the R&D demand and different keyword sublists, and combine the matching degrees of different keyword sublists to calculate the matching degree between the current resource attributes and the R&D demand. For example, for a project or paper, the matching between all sub-projects or all papers and the R&D demand is considered.

[0093] Sub-step S314, calculating the total distance between the R&D demand and the current keyword sub-list according to the first preset formula based on the plurality of distances.

[0094] In one implementation, the first preset formula is as follows:

[0095]

[0096] Among them, Si represents the total distance between the R&D demand and the i-th keyword sublist of the current resource attribute. Taking the project resource attribute as an example, Si is the distance between the R&D demand and the i-th sub-project. j represents the distance corresponding to the jth demand keyword that matches successfully, and m is the number of matches between the demand synonym tree of the demand keyword and the resource synonym tree of the current keyword sublist. j , that is, S j =S ab For example, when m=2, then S1=2*S1*S2 / (S1+S2).

[0097] Sub-step S315, then calculates the total distance between the R&D demand and the next keyword sub-list until all keyword sub-lists of the current resource attribute are traversed.

[0098] Sub-step S316, based on the total distance between the research and development needs and each keyword sub-list of the current resource attributes, calculate the matching degree between the research and development needs and the current resource attributes of the current teacher according to the second preset formula.

[0099] It can be understood that for each keyword sublist, the total distance between the R&D demand and it can be calculated according to the above sub-steps. Therefore, after obtaining the total distance between the R&D demand and each keyword sublist, for example, in one embodiment, the sum of the total distances of all keyword sublists can be used as the matching degree between the current resource attribute and the R&D demand. The specific formula is as follows:

[0100]

[0101] Among them, X represents the matching degree between the R&D demand and the current resource attributes of the current teacher, and n represents the total number of demand keywords. It can be understood that the matching degree of the three types of resource development, namely projects, papers and research fields, can be calculated separately according to the above sub-steps.

[0102] Step S400, calculating the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree.

[0103] In this embodiment, for the same teacher, the total matching degree between the teacher and the R&D needs will be calculated based on the matching degree of various resource attributes of the teacher. Before calculating the total matching degree, this embodiment also assigns weights to different resource attributes to reflect the importance of different resource attributes. For example, in one embodiment, the preset weights of the above-mentioned projects, papers, and research fields can satisfy the following relationship:

[0104] The preset weight ratio between adjacent item attributes is not less than a preset multiple. For example, the preset multiple may be 2 to 3. Specifically, if the 10-point system is taken as an example, the allocation method is: project is 8, paper is 4, research field is 2. Other allocation methods may also be used, such as 9, 3, 1, etc. It can be understood that in addition to the above-mentioned 10-point allocation method, the percentage system may also be used, which is not limited here.

[0105] Therefore, the calculation formula for a teacher's overall matching degree is as follows:

[0106] Y=Wp*Xp+Wt*Xt+Wf*Xf;

[0107] Among them, Y represents the overall matching degree of the teacher, Xp, Xt and Xf are the matching degrees of projects, papers and research fields respectively, and Wp, Wt and Wf are the preset weights of projects, papers and research fields respectively.

[0108] Step S500, sorting the total matching degrees of all teachers, and pushing information of a preset number of teachers with the highest matching degrees to the enterprise.

[0109] For each teacher, the above processing steps are used to obtain their respective total matching scores. Exemplarily, the total matching scores of all teachers can be sorted in descending or ascending order. If they are sorted in ascending order, the information of several teachers with the highest matching degree at the end of the queue will be fed back to the enterprise; if they are sorted in descending order, the information of several teachers with the highest matching degree at the front of the queue will be fed back to the enterprise, so as to further solve the problem that the enterprise cannot accurately and quickly search for matching teacher resources.

[0110] The resource push method proposed in this embodiment can help enterprises or university-enterprise docking departments or project undertaking departments to quickly find matching teachers so that they can participate in actual research and development production, thereby opening up the key links of industry-university-research cooperation and achieving teacher resource matching. Compared with manual resource search one by one and further screening and matching solutions, this method can greatly improve resource search efficiency and save a lot of labor costs and time.

[0111] Example 2

[0112] Please refer to Figure 5 Based on the method of the above embodiment 1, this embodiment proposes a teacher resource acquisition system 100. Exemplarily, the teacher resource acquisition system 100 includes:

[0113] The demand synonym tree acquisition module 110 is used to acquire the R&D demand of the enterprise and generate a demand synonym tree for each demand keyword in the R&D demand.

[0114] The resource synonym tree acquisition module 120 is used to classify each teacher information into different resource attributes and generate a resource synonym tree for each word in each resource attribute.

[0115] The synonym tree matching module 130 is used to calculate the matching degree of each resource attribute of the corresponding teacher according to the requirement synonym tree of each requirement keyword and all resource synonym trees of each resource attribute of the corresponding teacher.

[0116] The total matching degree calculation module 140 is used to calculate the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree.

[0117] The teacher resource acquisition module 150 is used to sort the total matching degrees of all teachers and push a preset number of teacher information with the highest matching degrees to the enterprise.

[0118] It can be understood that the device of this embodiment corresponds to the method of the above-mentioned embodiment 1, and the options in the above-mentioned embodiment 1 are also applicable to this embodiment, so they are not described repeatedly here.

[0119] The present application also provides a terminal device. Exemplarily, the terminal device includes a processor and a memory, wherein the memory stores a computer program, and the processor runs the computer program to enable the terminal device to execute the functions of each module in the above-mentioned teacher resource acquisition method or the above-mentioned teacher resource acquisition device.

[0120] The present application also provides a readable storage medium for storing the computer program used in the above-mentioned terminal device.

[0121] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and structure diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in an alternative implementation, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the structure diagram and / or the flow diagram, and the combination of boxes in the structure diagram and / or the flow diagram, can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0122] In addition, the functional modules or units in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0123] If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art, and the computer software product is stored in a storage medium, including several instructions for a computer device (which can be a smart phone, a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk.

[0124] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for acquiring teacher resources, characterized in that: include: Acquire the R&D needs of the enterprise, and generate a demand synonym tree for each demand keyword in the R&D needs; Classify each teacher's information into different resource attributes, and generate a resource synonym tree for each word in each resource attribute; Calculate the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher; Calculate the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree; Sorting the total matching degrees of all teachers, and pushing information of a preset number of teachers with the highest matching degrees to the enterprise; The different resource attributes include projects, papers and research fields of each teacher; each resource attribute is described by a corresponding keyword list, and the keyword list of the current resource attribute includes at least one keyword sublist, and each word in the keyword sublist has its own resource synonym tree; the matching degree of each resource attribute of the corresponding teacher is calculated according to the requirement synonym tree of each requirement keyword and all resource synonym trees of each resource attribute of the corresponding teacher, including: Searching in the resource synonym tree of the current keyword sublist of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword; If it is found in the resource synonym tree, it is determined that the current demand keyword is matched, and the distance between the words in the resource synonym tree and the words in the demand synonym tree of the found current keyword sublist is calculated; Then, the words in the demand synonym tree according to the current demand keyword are returned, and a search step is performed in the resource synonym tree of the current keyword sublist of the current resource attribute of the current teacher, until all demand keywords are traversed to obtain a number of distances; Calculating the total distance between the R&D demand and the current keyword sublist according to the first preset formula based on the plurality of distances, and then calculating the total distance between the R&D demand and the next keyword sublist until all keyword sublists of the current resource attribute are traversed; Calculate the matching degree between the research and development demand and the current resource attribute of the current teacher according to the second preset formula based on the total distance between each keyword sublist of the research and development demand and the current resource attribute; The acquisition of the distance between the words in the resource synonym tree and the words in the demand synonym tree includes: The position levels of the words in the resource synonym tree and the words in the demand synonym tree in their respective synonym trees are determined respectively, and the distance between the two words is calculated according to the following formula: S ab =k (Ha+Hb-2) ; Among them, S ab Indicates the distance between the two words corresponding to the current demand keyword, k is a preset value, Ha and Hb respectively represent the position levels of the two words in their respective synonym trees; Wherein, the first preset formula is as follows: ； Where Si represents the total distance between the i-th keyword sublist according to the R&D demand and the current resource attribute, S j represents the distance corresponding to the jth demand keyword, where m is the number of matches between the demand synonym tree and the resource synonym tree of the current keyword sublist; Wherein, the second preset formula is as follows: ； Among them, X represents the matching degree between the research and development demand and the current resource attribute of the current teacher, and n represents the total number of the demand keywords.

2. The teacher resource acquisition method according to claim 1, characterized in that: The calculation formula of the total matching degree of the corresponding teacher is as follows: Y=Wp*Xp+Wt*Xt+Wf*Xf; In the formula, Y represents the overall matching degree of the teacher, Xp, Xt and Xf are the matching degrees of the project, the paper and the research field respectively, Wp, Wt and Wf are the preset weights of the project, the paper and the research field respectively, and the ratio of Wp to Wt and the ratio of Wt to ​​Wf are not less than the preset multiples.

3. A teacher resource acquisition system, characterized in that: include: A demand synonym tree acquisition module is used to acquire the R&D demand of the enterprise and generate a demand synonym tree for each demand keyword in the R&D demand; A resource synonym tree acquisition module is used to classify each teacher's information into different resource attributes and generate a resource synonym tree for each word in each resource attribute; A synonym tree matching module, used for calculating the matching degree of each resource attribute of the corresponding teacher according to the demand synonym tree of each demand keyword and all resource synonym trees of each resource attribute of the corresponding teacher; A total matching degree calculation module, used for calculating the total matching degree of the corresponding teacher based on the preset weight of each resource attribute of the corresponding teacher and the matching degree; A teacher resource acquisition module, used to sort the total matching degrees of all teachers, and push information of a preset number of teachers with the highest matching degrees to the enterprise; The different resource attributes include projects, papers and research fields of each teacher; each resource attribute is described by a corresponding keyword list, and the keyword list of the current resource attribute includes at least one keyword sublist, and each word in the keyword sublist has its own resource synonym tree; the matching degree of each resource attribute of the corresponding teacher is calculated according to the requirement synonym tree of each requirement keyword and all resource synonym trees of each resource attribute of the corresponding teacher, including: Searching in the resource synonym tree of the current keyword sublist of the current resource attribute of the current teacher according to the words in the demand synonym tree of the current demand keyword; If it is found in the resource synonym tree, it is determined that the current demand keyword is matched, and the distance between the words in the resource synonym tree and the words in the demand synonym tree of the found current keyword sublist is calculated; Then, the words in the demand synonym tree according to the current demand keyword are returned, and a search step is performed in the resource synonym tree of the current keyword sublist of the current resource attribute of the current teacher, until all demand keywords are traversed to obtain a number of distances; Calculating the total distance between the R&D demand and the current keyword sublist according to the first preset formula based on the plurality of distances, and then calculating the total distance between the R&D demand and the next keyword sublist until all keyword sublists of the current resource attribute are traversed; Calculate the matching degree between the research and development demand and the current resource attribute of the current teacher according to the second preset formula based on the total distance between each keyword sublist of the research and development demand and the current resource attribute; The acquisition of the distance between the words in the resource synonym tree and the words in the demand synonym tree includes: The position levels of the words in the resource synonym tree and the words in the demand synonym tree in their respective synonym trees are determined respectively, and the distance between the two words is calculated according to the following formula: S ab =k (Ha+Hb-2) ; Among them, S ab Indicates the distance between the two words corresponding to the current demand keyword, k is a preset value, Ha and Hb respectively represent the position levels of the two words in their respective synonym trees; Wherein, the first preset formula is as follows: ； Where Si represents the total distance between the i-th keyword sublist according to the R&D demand and the current resource attribute, S j represents the distance corresponding to the jth demand keyword, where m is the number of matches between the demand synonym tree and the resource synonym tree of the current keyword sublist; Wherein, the second preset formula is as follows: ； Among them, X represents the matching degree between the research and development demand and the current resource attribute of the current teacher, and n represents the total number of the demand keywords.

4. A terminal device, characterized in that: The terminal device includes a processor and a memory, the memory stores a computer program, and the processor is used to execute the computer program to implement the teacher resource acquisition method according to any one of claims 1-2.

5. A readable storage medium, characterized in that: It stores a computer program, which, when executed on a processor, implements the teacher resource acquisition method according to any one of claims 1-2.

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