Talent emotional tendency judgment method and system based on emotional word matching and medium

Abstract

The invention discloses a talent emotional tendency judgment method and system based on emotional word matching and a medium, and the method comprises the following steps: obtaining identity information of a target person, and preliminarily retrieving a social network user name of the target person based on the identity information of the target person; verifying the social network user name of the preliminary retrieval target person based on a verification condition to obtain a verification result; determining a final social network user name; public associated contents of the social network platform are obtained, and keywords are extracted; performing emotion recognition on the keywords based on an intelligent semantic analysis rule to obtain emotion information, and analyzing talent emotion tendency judgment on the target personnel based on the emotion information to obtain a judgment result; according to the method, emotion recognition is carried out on the keywords through the intelligent semantic analysis rule to obtain emotion information, the talent emotion tendency of the to-be-evaluated talent is determined through the emotion tendency radar map, and the accuracy and stability of the talent emotion tendency analysis result are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of talent evaluation, and in particular to a talent emotional tendency judgment method, system and medium based on emotional word matching. Background Art

[0002] Emotional tendency is the subjective inner likes and dislikes and inner evaluation of a certain object, which has degree and objectivity. Emotion is a part of attitude, which is consistent with the inner feelings and intentions in attitude. It is a complex and stable physiological evaluation and experience of attitude. Emotion includes moral sense and sense of value.

[0003] At present, the recognition of word sentiment tendency is relatively mature. Obtaining useful tendency information and knowledge for text content has become a research hotspot in natural language processing. Methods and technologies for sentiment word recognition and sentiment word polarity discrimination have been formed. There are methods for obtaining the tendency of sentiment words by using numerical calculations, sentiment word tendencies using constructed seed sentiment words, and sentiment word tendencies calculated based on the properties of conjunctions; there are also sentiment tendency analysis methods based on sentiment dictionary methods, which give a sentiment concept dictionary, determine the degree of influence of different types of sentiment words on text sentiment by calculating vocabulary similarity, and design a sentiment scoring strategy to accurately analyze the sentiment tendency of the text.

[0004] The current methods only study the matching between sentiment words and sentiment tendencies, without considering the sources and related sources of sentiment words, and there is no assessment and judgment of sentiment tendencies for talent evaluation. Summary of the invention

[0005] The purpose of the present invention is to provide a talent emotional tendency judgment method based on emotional word matching, comprising the following steps:

[0006] Obtain the identity information of the target person, and preliminarily retrieve the social network user name of the target person based on the identity information of the target person;

[0007] Verify the social network user name of the preliminary search target person based on the verification condition to obtain a verification result;

[0008] Determine the target person’s final social network username based on the verification results;

[0009] Obtain the publicly available content on the social network platform based on the target person’s final social network username and extract keywords;

[0010] Based on the intelligent semantic analysis rules, the keywords are sentimentally identified to obtain sentiment information, and the target personnel are analyzed and judged for their sentiment tendencies based on the sentiment information to obtain the judgment results.

[0011] Furthermore, the identity information of the target person is obtained, and the social network user name of the target person is initially retrieved based on the identity information of the target person, specifically including:

[0012] Obtain the identity information of the target person, including the institution where the target person works, identity characteristics, and social circle relationships;

[0013] Analyze one or more social platforms that the target person has used historically based on their institution, identity characteristics, and social circle relationships;

[0014] Obtaining registration information of target persons based on one or more historically used social platforms;

[0015] The target person's social network username is initially retrieved based on the target person's registration information.

[0016] Furthermore, the target person's final social network username is determined based on the verification result, including:

[0017] According to the organization, identity characteristics and social circle of the talent to be evaluated, search and preliminarily determine the user name of the target person on the social networking platform;

[0018] Obtain the time and location of the target person's public content on the social platform, and conduct statistical analysis and verification on the time and location of the public content to obtain the verification results;

[0019] Analyze the match between the target person's user name and the time and location of the public content based on the verification results;

[0020] If the matching degree is greater than or equal to the set matching degree threshold, the target person's final social network username is determined;

[0021] If the matching degree is less than the set matching degree threshold, the user name of the target person will be re-screened.

[0022] Furthermore, based on the target person's final social network username, the publicly available related content on the social network platform is obtained, and keywords are extracted, including:

[0023] Retrieve relevant content published, forwarded and liked by the target person on social networking platforms based on big data technology;

[0024] Extract features of the related content to obtain content features;

[0025] Normalize the content features to obtain a processing result;

[0026] Keywords are extracted based on the processing results.

[0027] Furthermore, based on the intelligent semantic analysis rules, sentiment recognition is performed on keywords to obtain sentiment information, including:

[0028] Obtain keywords, perform semantic recognition on keywords based on intelligent semantic analysis rules, and obtain semantic recognition information;

[0029] Perform language sense recognition based on semantic recognition information to obtain language sense information;

[0030] Analyze semantic sentiment based on language sense information to obtain emotional information.

[0031] Furthermore, based on the emotional information, the target personnel are analyzed to determine their emotional tendencies and obtain the judgment results, which specifically include:

[0032] Extract sentiment words based on sentiment information, and classify and match sentiment words with keywords of public related content based on the public opinion expert analysis network to obtain matching results;

[0033] The emotional tendency radar chart is determined based on the matching results, and the emotional tendency of the talent is judged based on the emotional tendency radar chart to obtain the judgment result.

[0034] The present invention also provides a talent emotional tendency judgment system based on emotional word matching, comprising a processor, a memory and at least one program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes instructions for executing the talent emotional tendency judgment method based on emotional word matching as described in any one of the above items.

[0035] The present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program enables a computer to execute to implement any of the above-mentioned methods for judging the emotional tendency of talents based on emotional word matching.

[0036] Due to the application of the above technical solution, the present invention has the following advantages compared with the prior art:

[0037] The present invention determines the user name of the talent to be evaluated in the social networking platform, collects the text content publicly published, forwarded and liked by the talent to be evaluated in the social networking platform, performs sentiment recognition on keywords through intelligent semantic analysis rules to obtain sentiment information, and determines the talent's sentiment tendency through a sentiment tendency radar chart, thereby effectively improving the accuracy and stability of the talent's sentiment tendency analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of a method for judging the emotional tendency of talents based on emotional word matching provided by an embodiment of the present invention is shown;

[0039] Figure 2A flowchart of a method for initially retrieving the social network user name of a target person in the talent sentiment tendency judgment method based on sentiment word matching provided in this embodiment is shown;

[0040] Figure 3 A flow chart of determining the final social network user name of a target person in the talent sentiment tendency judgment method based on sentiment word matching provided in this embodiment is shown. DETAILED DESCRIPTION

[0041] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described 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, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0042] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0043] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0044] like Figure 1-Figure 3 As shown, the embodiment of the present invention provides a method for judging the emotional tendency of talents based on emotional word matching, comprising the following steps:

[0045] S101, obtaining identity information of a target person, and preliminarily retrieving a social network user name of the target person based on the identity information of the target person;

[0046] S102, verifying the social network user name of the preliminary search target person based on the verification condition to obtain a verification result;

[0047] S103, determining the target person's final social network user name based on the verification result;

[0048] S104, obtaining public related content on the social network platform based on the target person's final social network user name, and extracting keywords;

[0049] S105, based on the intelligent semantic analysis rules, sentiment recognition is performed on the keywords to obtain sentiment information, and based on the sentiment information, the target personnel are analyzed to determine their sentiment tendency and obtain a determination result.

[0050] According to an embodiment of the present invention, obtaining the identity information of a target person and preliminarily retrieving the social network user name of the target person based on the identity information of the target person specifically includes:

[0051] S201, obtaining the identity information of the target person, the identity information of the target person includes the institution where he / she works, identity characteristics and relationship in the circle of friends;

[0052] S202, analyzing one or more social platforms used historically by the target person based on the target person's institution, identity characteristics, and social circle associations;

[0053] S203, obtaining registration information of the target person based on one or more historically used social platforms;

[0054] S204: Preliminarily retrieve the social network user name of the target person based on the registration information of the target person.

[0055] According to an embodiment of the present invention, determining the final social network user name of the target person based on the verification result specifically includes:

[0056] S301, searching and preliminarily determining the user name of the target person in the social networking platform according to the organization, identity characteristics and friend circle association of the talent to be evaluated;

[0057] S302, obtaining the time and location of the target person's public content on the social platform, and performing statistical analysis and verification on the time and location of the public content to obtain a verification result;

[0058] S303, analyzing the matching degree between the user name of the target person and the time and location of the public content based on the verification result;

[0059] S304, if the matching degree is greater than or equal to the set matching degree threshold, determining the final social network user name of the target person;

[0060] S305: If the matching degree is less than the set matching degree threshold, the user name of the target person is re-screened.

[0061] According to an embodiment of the present invention, obtaining the public related content on the social network platform based on the target person's final social network user name and extracting keywords specifically includes:

[0062] Retrieve relevant content published, forwarded and liked by the target person on social networking platforms based on big data technology;

[0063] Extract features of the related content to obtain content features;

[0064] Normalize the content features to obtain a processing result;

[0065] Keywords are extracted based on the processing results.

[0066] According to an embodiment of the present invention, emotion recognition is performed on keywords based on intelligent semantic analysis rules to obtain emotion information, which specifically includes:

[0067] Obtain keywords, perform semantic recognition on keywords based on intelligent semantic analysis rules, and obtain semantic recognition information;

[0068] Perform language sense recognition based on semantic recognition information to obtain language sense information;

[0069] Analyze semantic sentiment based on language sense information to obtain emotional information.

[0070] According to an embodiment of the present invention, the target personnel are analyzed for emotional tendency judgment based on emotional information to obtain a judgment result, which specifically includes:

[0071] Extract sentiment words based on sentiment information, and classify and match sentiment words with keywords of public related content based on the public opinion expert analysis network to obtain matching results;

[0072] The emotional tendency radar chart is determined based on the matching results, and the emotional tendency of the talent is judged based on the emotional tendency radar chart to obtain the judgment result.

[0073] To sum up, the present invention determines the user name of the talent to be evaluated in the social networking platform, collects the text content publicly published, forwarded and liked by the talent to be evaluated in the social networking platform, performs sentiment recognition on keywords through intelligent semantic analysis rules to obtain sentiment information, and determines the talent emotional tendency of the talent to be evaluated through the emotional tendency radar chart, thereby effectively improving the accuracy and stability of the talent emotional tendency analysis results.

[0074] This embodiment also provides a talent emotional tendency judgment system based on emotional word matching, including a processor, a memory and at least one program, the program is stored in the memory and is configured to be executed by the processor, and the program includes instructions for executing any of the above-mentioned talent emotional tendency judgment methods based on emotional word matching.

[0075] Those skilled in the art will appreciate that, for ease of description, the example in which both the memory and the processor are provided with one is used for description. In an actual terminal or server, there may be multiple processors and memories. The memory may also be referred to as a storage medium or a storage device, etc., which is not limited in the embodiments of the present application.

[0076] It should be understood that in the embodiments of the present application, the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor may also be a general-purpose microprocessor, graphics processing unit (GPU), or one or more integrated circuits for executing related programs to implement the functions required to be executed in the embodiments of the present application.

[0077] The processor can also be an integrated circuit chip with signal processing capabilities. In the implementation process, the various steps of the present application can be completed by the integrated logic circuit of the hardware in the processor or the instructions in the form of software. The above-mentioned processor can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The steps of the method disclosed in the embodiments of the present application can be directly embodied as a hardware decoding processor to be executed, or a combination of hardware and software modules in the decoding processor to be executed. The software module can be located in a random access memory, a flash memory and a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register and other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory, and combines its hardware to complete the functions required to be performed by the unit included in the method, device and storage medium of the embodiment of the present application.

[0078] It should also be understood that the memory mentioned in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache.

[0079] By way of example but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct memory bus random access memory (Direct Rambus RAM, DR RAM).

[0080] The memory may also be a read-only optical disc (Compact Disc Read-Only Memory, CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be independent and connected to the processor via a bus. The memory may also be integrated with the processor, and the memory may store a program. When the program stored in the memory is executed by the processor, the processor is used to execute the various steps of the determination method in the above-mentioned embodiment of the present application.

[0081] It should be noted that when the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, the memory (storage module) is integrated into the processor. It should be noted that the memory described herein is intended to include but is not limited to these and any other suitable types of memory.

[0082] It should be understood that the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0083] In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in a processor or an instruction in the form of software. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor for execution, or a combination of hardware and software modules in a processor for execution. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in a memory, and the processor reads the information in the memory, and completes the steps of the above method in conjunction with its hardware. To avoid repetition, it is not described in detail here.

[0084] Those skilled in the art will appreciate that the various illustrative logical blocks (ILBs) and steps described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0085] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a program product of computer programming. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a processor, all or part of the processes or functions according to the embodiments of the present application are generated. The computer may be a general-purpose computer, a computer network, or other programmable device.

[0086] This embodiment also provides a computer-readable storage medium, which stores a computer program. The computer program enables a computer to execute to implement the above-mentioned talent emotional tendency judgment method based on emotional word matching.

[0087] It should be noted that computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber) or wireless (e.g., infrared, wireless, microwave, etc.) means, or can be transmitted from one website, computer, server or data center to a mobile phone processor by wired means. Computer-readable storage media can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disk, hard disk), optical media (e.g., DVD), or semiconductor media (e.g., solid-state hard disk), etc.

[0088] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments, or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A talent emotional tendency judgment method based on emotional word matching, characterized in that: The following steps are involved: Obtain the identity information of the target person, and preliminarily retrieve the social network user name of the target person based on the identity information of the target person; Verify the social network user name of the preliminary search target person based on the verification condition to obtain a verification result; Determine the target person’s final social network username based on the verification results; Obtain the publicly available content on the social network platform based on the target person’s final social network username and extract keywords; Based on the intelligent semantic analysis rules, the keywords are sentimentally identified to obtain sentiment information, and the target personnel are analyzed and judged for their sentiment tendencies based on the sentiment information to obtain the judgment results.

2. The talent emotional tendency judgment method based on emotional word matching according to claim 1 is characterized in that: Obtain the target person's identity information and initially retrieve the target person's social network username based on the target person's identity information, including: Obtain the identity information of the target person, including the institution where the target person works, identity characteristics, and social circle relationships; Analyze one or more social platforms that the target person has used historically based on their institution, identity characteristics, and social circle relationships; Obtaining registration information of target persons based on one or more historically used social platforms; The target person's social network username is initially retrieved based on the target person's registration information.

3. The talent emotional tendency judgment method based on emotional word matching as claimed in claim 2 is characterized in that: Determine the target person’s final social network username based on the verification results, including: According to the organization, identity characteristics and social circle of the talent to be evaluated, search and preliminarily determine the user name of the target person on the social networking platform; Obtain the time and location of the target person's public content on the social platform, and conduct statistical analysis and verification on the time and location of the public content to obtain the verification results; Analyze the match between the target person's user name and the time and location of the public content based on the verification results; If the matching degree is greater than or equal to the set matching degree threshold, the target person's final social network username is determined; If the matching degree is less than the set matching degree threshold, the user name of the target person will be re-screened.

4. The talent emotional tendency judgment method based on emotional word matching as claimed in claim 3 is characterized in that: Obtain the publicly available content on the social network platform based on the target person’s final social network username and extract keywords, including: Retrieve relevant content published, forwarded and liked by the target person on social networking platforms based on big data technology; Extract features of the related content to obtain content features; Normalize the content features to obtain a processing result; Keywords are extracted based on the processing results.

5. The talent emotional tendency judgment method based on emotional word matching as claimed in claim 1 is characterized in that: Based on the intelligent semantic analysis rules, the keywords are sentimentally identified to obtain sentiment information, including: Obtain keywords, perform semantic recognition on keywords based on intelligent semantic analysis rules, and obtain semantic recognition information; Perform language sense recognition based on semantic recognition information to obtain language sense information; Analyze semantic sentiment based on language sense information to obtain emotional information.

6. The talent emotional tendency judgment method based on emotional word matching according to claim 1 is characterized in that: Based on the emotional information, the target personnel are analyzed for emotional tendencies and judgments are made to obtain the judgment results, including: Extract sentiment words based on sentiment information, and classify and match sentiment words with keywords of public related content based on the public opinion expert analysis network to obtain matching results; The emotional tendency radar chart is determined based on the matching results, and the emotional tendency of the talent is judged based on the emotional tendency radar chart to obtain the judgment result.

7. A talent emotional tendency judgment system based on emotional word matching, characterized in that: It includes a processor, a memory and at least one program, wherein the program is stored in the memory and is configured to be executed by the processor, and the program includes instructions for executing the talent emotional tendency judgment method based on emotional word matching as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which enables a computer to execute to implement the talent emotional tendency judgment method based on emotional word matching according to any one of claims 1 to 6.

Images