A method and device for evaluating the degree of matching between personnel and positions

Abstract

The present application provides a method and device for evaluating the degree of match between personnel and positions, including obtaining physiological information of a first person in a target game scene, wherein the target game scene corresponds to a target position and is used to induce the emotions of the first person; determining a first emotional state parameter based on the physiological information; and evaluating the degree of match between the first person and the target position based on the first emotional state parameter. The evaluation method provided in the present application can objectively and accurately evaluate the degree of match between personnel and positions, so that the human resources department can more accurately screen out suitable candidates for the position, improve work efficiency, and save labor costs. In addition, the evaluation method provided in the present application can also objectively and accurately evaluate the degree of tacit understanding between personnel, so that personnel can more accurately and efficiently screen out personnel who share the same ideals or have complementary emotions with themselves.

Description

Technical Field

[0001] The present application relates to the technical field of job matching, and in particular to a method and device for evaluating the degree of matching between personnel and jobs. Background Art

[0002] Emotions are normal physiological reactions, but overly agitated or dull emotional reactions may harm our physical and mental health, work, and even social stability. Normal emotional reactions to specific scenarios and the ability to regulate / manage them are also one of the competency characteristics required for many jobs. That is, different positions require different emotional abilities. Only when job seekers have the emotional abilities required for the position can they be better qualified for the job. For example, kindergarten teachers need to be patient when facing children, and special forces soldiers need to be calm when facing terrorist attacks.

[0003] At present, when human resources departments select or identify personnel based on competency characteristic models, they mainly evaluate candidates through interviews or questionnaires, but this method is relatively subjective and lacks empirical basis. On the other hand, real work (probation period) and trial communication often require greater time and financial costs, which means that it is difficult for human resources departments to accurately screen out personnel that match the position in a short period of time. Summary of the invention

[0004] The present application provides a method and device for evaluating the degree of matching between personnel and positions, which can objectively and accurately evaluate the degree of matching between personnel and positions, so that the human resources department can more accurately screen suitable candidates for the positions, improve work efficiency, and save labor costs.

[0005] In a first aspect, a method for evaluating the degree of match between a person and a position is provided, comprising obtaining physiological information of a first person in a target game scenario, wherein the target game scenario corresponds to a target position and is used to induce emotions of the first person; determining a first emotional state parameter based on the physiological information; and evaluating the degree of match between the first person and the target position based on the first emotional state parameter.

[0006] In combination with the first aspect, in certain implementations of the first aspect, evaluating the degree of match between the first person and the target position based on the first emotional state parameter includes evaluating the degree of match between the first person and the target position based on the first emotional state parameter and a preset emotional state parameter.

[0007] In combination with the first aspect, in certain implementations of the first aspect, the first emotional state parameters include n evaluation parameters, the preset emotional state parameters include n preset evaluation parameters, the n evaluation parameters correspond one-to-one to the n preset evaluation parameters, and n is an integer greater than or equal to 1; evaluating the degree of match between the first person and the target position based on the first emotional state parameters and the preset emotional state parameters includes determining the ratio of each of the n evaluation parameters to the corresponding preset evaluation parameters to obtain n ratios; evaluating the degree of match between the first person and the target position based on the n ratios.

[0008] In combination with the first aspect, in certain implementations of the first aspect, evaluating the degree of match between the first person and the target position based on the n ratios includes determining the degree of match between the first person and the target position based on an adaptation value and a preset threshold, wherein the adaptation value is the sum of each ratio of the n ratios multiplied by a corresponding weight value.

[0009] In combination with the first aspect, in certain implementations of the first aspect, the preset emotional state parameter is a second emotional state parameter determined based on physiological information of the second person in the target game scenario.

[0010] In combination with the first aspect, in certain implementations of the first aspect, before obtaining the physiological information of the first person in the target game scene, the evaluation method also includes determining the object of interest of the first person based on the eye movement information of the first person in a preset game scene; determining the target position based on the object of interest; and determining the target game scene based on the target position.

[0011] In combination with the first aspect, in certain implementations of the first aspect, determining the first emotional state parameter based on the physiological information includes inputting the physiological information into a pre-trained deep learning model, and determining the first emotional state parameter based on an output value of the deep learning model.

[0012] In combination with the first aspect, in certain implementations of the first aspect, the first emotional state parameter includes at least one of the following evaluation parameters: emotional efficacy value, emotional arousal value, peak value of emotional efficacy value, peak value of emotional arousal value, recovery time of emotional efficacy value, and recovery time of emotional arousal value.

[0013] In combination with the first aspect, in certain implementations of the first aspect, the physiological information includes at least one of the following information: facial expression information, micro-expression information, heart rate information, heart rate variability information, skin resistance information, and brain wave information.

[0014] According to the evaluation method for the degree of matching between personnel and positions provided in the embodiment of the present application, the evaluation device first obtains the physiological information of the personnel in the target game scene, then determines the emotional state parameters through the physiological information, and objectively evaluates the degree of matching between the personnel and the target position based on the emotional state parameters, so that the human resources department can screen out suitable candidates for the position through the matching degree. Compared with the method of determining emotional state parameters through interviews or questionnaires in the prior art, the method of determining emotional state parameters through the physiological information of personnel in the target game scene in the embodiment of the present application is more objective and more efficient, that is, the evaluation method provided by the present application can objectively and efficiently evaluate the degree of matching between personnel and the target position, so that the human resources department can more accurately screen out suitable candidates for the position, and can improve the work efficiency of the human resources department and save labor costs.

[0015] In a second aspect, a device for evaluating the degree of match between personnel and positions is provided, including an acquisition module for acquiring physiological information of a first person in a target game scene, wherein the target game scene corresponds to a target position and is used to induce emotions of the first person; a determination module for determining a first emotional state parameter based on the physiological information; and an evaluation module for evaluating the degree of match between the first person and the target position based on the first emotional state parameter.

[0016] In combination with the second aspect, in certain implementations of the second aspect, the evaluation module is specifically used to: evaluate the degree of match between the first person and the target position based on the first emotional state parameter and a preset emotional state parameter.

[0017] In combination with the second aspect, in certain implementations of the second aspect, the first emotional state parameters include n evaluation parameters, the preset emotional state parameters include n preset evaluation parameters, the n evaluation parameters correspond one-to-one to the n preset evaluation parameters, and n is an integer greater than or equal to 1; the evaluation module is specifically used to: determine the ratio of each of the n evaluation parameters to the corresponding preset evaluation parameter to obtain n ratios; and evaluate the degree of match between the first person and the target position based on the n ratios.

[0018] In combination with the second aspect, in certain implementations of the second aspect, the evaluation module is specifically used to: determine the degree of match between the first person and the target position based on the adaptation value and a preset threshold, wherein the adaptation value is the sum of each of the n ratios multiplied by the corresponding weight value.

[0019] In combination with the second aspect, in certain implementations of the second aspect, the preset emotional state parameter is a second emotional state parameter determined based on physiological information of the second person in the target game scenario.

[0020] In combination with the second aspect, in certain implementations of the second aspect, the determination module is also used to: determine the object of interest of the first person based on the eye movement information of the first person in a preset game scene; determine the target position based on the object of interest; determine the target game scene based on the target position.

[0021] In combination with the second aspect, in certain implementations of the second aspect, the determination module is specifically used to: input the physiological information into a pre-trained deep learning model, and determine the first emotional state parameter according to an output value of the deep learning model.

[0022] In combination with the second aspect, in certain implementations of the second aspect, the first emotional state parameter includes at least one of the following evaluation parameters: emotional efficacy value, emotional arousal value, peak value of emotional efficacy value, peak value of emotional arousal value, recovery time of emotional efficacy value, and recovery time of emotional arousal value.

[0023] In combination with the second aspect, in certain implementations of the second aspect, the physiological information includes at least one of the following information: facial expression information, micro-expression information, heart rate information, heart rate variability information, skin resistance information, and brain wave information.

[0024] In a third aspect, a device for evaluating the degree of matching between personnel and positions is provided, comprising at least one processor, wherein the at least one processor is used to couple with a memory, read and execute instructions in the memory, so as to implement the evaluation method provided by any one of the implementation modes in the first aspect above.

[0025] In a fourth aspect, a system for evaluating the degree of matching between personnel and positions is provided, comprising a display device for displaying game scenes; a collection device for collecting physiological information of personnel; and an evaluation device provided by any one of the implementation methods of the second aspect or the third aspect, wherein the evaluation device is communicatively connected to the collection device.

[0026] In a fifth aspect, a computer program product is provided, the computer program product comprising: a computer program code, when the computer program code is run on a computer, the computer executes the evaluation method provided by any one of the implementations in the first aspect above.

[0027] It should be noted that the above-mentioned computer program code can be stored in whole or in part on a storage medium, wherein the storage medium can be packaged together with the processor or separately from the processor, and this application does not make any specific limitation on this.

[0028] In a sixth aspect, a computer-readable medium is provided, wherein the computer-readable medium stores a program code, and when the computer program code is executed on a computer, the computer executes the evaluation method provided by any one of the implementations in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0030] Figure 1 It is a schematic diagram of a system architecture applicable to the evaluation method provided in the embodiment of the present application.

[0031] Figure 2 It is a schematic diagram of a two-dimensional emotion model provided in an embodiment of the present application.

[0032] Figure 3 It is a schematic flow chart of the evaluation method provided in the embodiment of the present application.

[0033] Figure 4 It is a schematic flow chart of the specific implementation process of the evaluation method provided in the embodiment of the present application.

[0034] Figure 5 It is a schematic flow chart of an evaluation method provided in another embodiment of the present application.

[0035] Figure 6 It is a schematic block diagram of an evaluation device provided in an embodiment of the present application.

[0036] Figure 7 It is a structural schematic diagram of the evaluation device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0037] The technical solution in the present application will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0038] The technical solution in the present application will be described below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0039] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0040] The term "include" herein indicates the presence of the described features, integral bodies, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integral bodies, steps, operations, elements, components and / or their collections. The terms "include", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0041] In this article, the term "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0042] A competency model is a competency structure that combines the requirements for excellent performance in a specific position. It is an important foundation for a series of human resource management and development practices. The competencies required of employees in different positions in an organization are different. In different organizations and industries, the competency characteristics of employees in the same or similar positions are also different. Here, the sum of competencies required for a specific task role is called a competency model.

[0043] Normal emotional reactions and the ability to regulate / manage emotions in specific scenarios (such as the ability to withstand stress, etc.) are also one of the competency characteristics required for many positions. That is, different positions may require different emotional reactions and their regulation / management abilities. For example, kindergarten teachers, nursing home staff, nurses, civil servants, waiters, nuclear power plant employees, police, judges, or special forces may have different requirements for emotional reactions and their management abilities.

[0044] At present, human resources departments mainly test the competence of job seekers through interviews or questionnaires in order to assess whether job seekers are qualified for the positions. However, this method is subjective, and the evaluation results are often affected by the subjective bias of the interviewer and lack empirical evidence. On the other hand, real work (probation period) often requires more time and resource costs, that is, human resources departments cannot accurately screen out job seekers who match the positions in a short period of time.

[0045] In view of this, an embodiment of the present application provides an evaluation method for the degree of match between personnel and positions. The evaluation method is executed by an evaluation device. The evaluation method determines emotional state parameters by utilizing the physiological information of personnel in game scenarios (various simulated scenarios that can induce emotions in personnel), and evaluates the degree of match between personnel and positions based on the emotional state parameters, so that the human resources department can objectively and accurately understand the degree of match between personnel and positions in a short period of time, thereby being able to more accurately screen suitable candidates for the positions, improve efficiency, and save labor costs.

[0046] The following first describes the system architecture involved in the embodiments of the present application.

[0047] Figure 1 Schematic diagram of a system architecture applicable to the method for evaluating the degree of matching between personnel and positions provided in the embodiment of the present application. Figure 1 As shown, the evaluation system 100 includes a display device 110 , a collection device 120 and an evaluation device 130 .

[0048] The display device 110 is used to display different game scenes, and the game scenes are used to induce emotions of personnel, such as happiness, anger, missing, sadness, fear, and surprise. The collection device 120 is used to collect physiological information of personnel in game scenes, such as heart rate information, heart rate variability information, facial expression information, micro-expression information, skin resistance information, and brain wave information. The evaluation device 130 is connected to the collection device 120 in communication, and is used to determine the emotional state parameters of the personnel according to the acquired physiological information, and objectively evaluate the matching degree between the personnel and the position according to the emotional state parameters.

[0049] Optionally, the display device 110 may be a terminal device with a display screen, such as a mobile phone or a computer.

[0050] Optionally, the collection device 120 may include at least one of the following devices: an eye tracker for collecting eye movement information, a smart bracelet for collecting heart rate information and heart rate variability information, and a camera for collecting facial expression information and micro-expression information, but is not limited thereto.

[0051] Optionally, the evaluation device 130 may be a control host or a cloud server, and may also be an intelligent electronic device such as a mobile phone or a tablet computer. The evaluation device 130 and the collection device 120 are connected to each other by wire or wireless communication.

[0052] Figure 2 Schematic diagram of a two-dimensional emotion model provided in the embodiment of the present application. Figure 2 As shown, the embodiments of the present application can describe a person's emotional state (emotional response and its management ability) from two dimensions: valence (referring to the type of emotion, such as happiness or fear, etc.) and arousal (referring to the extent to which the emotion is activated, such as excessive agitation or insufficient arousal, etc.).

[0053] The embodiment of the present application can quantitatively express the emotional state of a person through a two-dimensional emotional model. For example, the value range of each dimension is between 1 and 9 points, that is, the emotional state of a person is represented by an emotional efficacy value and an emotional arousal value, where the emotional efficacy value and the emotional arousal value are integers.

[0054] Among them, professional psychologists can understand the emotional state of people through physiological information such as facial expressions, micro-expressions, heart rate and heart rate variability, and Figure 2 The two-dimensional emotion model shown expresses the emotional state of a person quantitatively, that is, a professional psychologist can evaluate the emotional efficacy value of a person through the facial expression images and micro-expression images of the person collected by a camera with high temporal and spatial resolution, and evaluate the emotional arousal value of a person through the heart rate data and heart rate variability data of the person collected by a smart bracelet, and quantitatively express the emotional state of a person from the two dimensions of emotional efficacy value and emotional arousal value.

[0055] For example, if a professional psychologist learns from physiological information that a person is in a happy mood, the person's emotional state can be quantified by an emotional efficacy value of 7 points and an emotional arousal value of 8 points.

[0056] Figure 3 is a schematic flow chart of the evaluation method provided in the embodiment of the present application. Figure 3 The evaluation method 300 provided in the embodiment of the present application is described. The method 300 includes:

[0057] Step S310, obtaining physiological information of the first person in a target game scene, where the target game scene corresponds to a target position and is used to induce emotions of the first person.

[0058] Specifically, different positions require different emotional states. By obtaining the physiological information of personnel, the emotional state of the personnel can be understood so as to evaluate whether the personnel are competent for the position. Optionally, the physiological information includes at least one of the following information: heart rate information, heart rate variability information, facial expression information, micro-expression information, skin resistance information or brain wave information, but not limited to this.

[0059] Optionally, the evaluation device 130 may obtain the physiological information of the person through a collection device 120 (eg, a camera, a smart bracelet, etc.).

[0060] For example, the evaluation device 130 receives a message sent by the collection device 120 via 5G or a wireless network, and the message carries the physiological information collected by the collection device 120 .

[0061] Among them, the game scene can induce the emotional state of people by simulating various scenes related to joy, anger, sorrow, happiness, fear and so on in work or life. The target game scene is the game scene corresponding to the target position. People can be induced to have emotional states related to the target position in the target game scene. The target position can be a recruitment position, and the first person can be any person (such as a job seeker, etc.).

[0062] Exemplarily, the game scenes may be scenes of interacting with children, scenes of children crying, scenes of interacting with elderly people in nursing homes, scenes of elderly people falling down, scenes of doing experiments, scenes of lawsuits, scenes of sorting out accounts, scenes of chasing criminals, scenes of terrorist attacks, scenes of facing emergencies, scenes of fires, scenes of visiting zoos, scenes of animals fighting, etc.

[0063] Step S320: determining a first emotional state parameter according to the physiological information.

[0064] Among them, the first emotional state parameter is an emotional state parameter determined according to the physiological information of the first person in the target game scene.

[0065] As can be seen from the foregoing, the emotional state of a person can be determined through physiological information, and the emotional state can be quantified through emotional state parameters (such as emotional efficacy value, emotional arousal value, etc.).

[0066] The emotional state parameter may include at least one evaluation parameter. Optionally, the emotional state parameter includes at least one of the following evaluation parameters: emotional potency value, emotional arousal value, peak value of emotional potency value, peak value of emotional arousal value, recovery time of emotional potency value and recovery time of emotional arousal value.

[0067] After the evaluation device 130 obtains the physiological information, it can determine which one or more evaluation parameters (such as emotional efficacy value or emotional arousal value, etc.) the emotional state parameters include based on the physiological information. This application does not impose any limitation on how the evaluation device 130 determines the emotional state parameters based on the physiological information.

[0068] Optionally, the emotional state parameter may be determined according to a preset logical algorithm.

[0069] Optionally, the emotional state parameter may be determined based on pre-stored historical data.

[0070] Optionally, the emotional state parameters may be determined based on physiological information and a preset mapping relationship table between physiological information and emotional state parameters.

[0071] For example, the evaluation device 130 may determine a unique preset heart rate data range based on the acquired heart rate data, and then determine the person's emotional effectiveness value based on a mapping relationship table between the unique preset heart rate data range and the emotional effectiveness value.

[0072] Optionally, the evaluation device 130 may input the physiological information into a pre-trained deep learning model, and determine the first emotional state parameter according to an output value of the deep learning model.

[0073] Specifically, deep learning is a subcategory of machine learning, and its core is deep neural network, which can be understood as an artificial neural network structure containing multiple hidden layers, which enables computers to interpret data by simulating the working method of the human brain and find patterns in the data for prediction or classification.

[0074] Here, the evaluation device 130 will pre-process the acquired physiological information of the person (filtering and noise reduction, artifact removal, baseline correction, etc.), and then perform feature extraction and feature selection on the pre-processed physiological information to determine the physiological information feature vector. Professional psychologists can determine the emotional state parameters through physiological information and two-dimensional emotional models. At this time, the emotional state parameters can be marked on the acquired physiological information feature vector to establish a complete sample. By analogy, a large number of samples can be obtained to build a sample database, and the samples in the database are divided into training samples and test samples. The physiological information feature vector in the training sample is used as an input variable, and the corresponding emotional state parameters are used as output variables to train the deep learning model, and the accuracy of the trained deep learning model is verified by the physiological information feature vector and the corresponding emotional state parameters in the test sample. Finally, the newly acquired physiological information feature vector is input into the pre-trained deep learning model, and the emotional state parameters are determined according to the output value of the deep learning model.

[0075] Exemplarily, the acquired heart rate information, heart rate variability information, facial expression information and micro-expression information are preprocessed to obtain a heart rate information feature vector, a heart rate variability information feature vector, a facial expression information feature vector and a micro-expression information feature vector, the heart rate information feature vector and the heart rate variability information feature vector are input into a pre-trained deep learning model, and the emotion effectiveness value is determined according to the output value of the deep learning model, the facial expression information feature vector and the micro-expression information feature vector are input into a pre-trained deep learning model, and the emotion arousal value is determined according to the output value of the deep learning model.

[0076] Step S330: evaluating the matching degree between the first person and the target position according to the first emotional state parameter.

[0077] Optionally, the matching degree between the person and the target position is evaluated based on the emotional state parameters and preset emotional state parameters.

[0078] For example, the matching degree between a person and a target position is evaluated based on the emotional state parameters and a mapping relationship table between preset emotional state parameters and matching degrees.

[0079] For example, the degree of match between a person and a target position is evaluated based on the difference between the emotional state parameter and the preset emotional state parameter.

[0080] For another example, the degree of match between a person and a target position is evaluated based on the ratio of an emotional state parameter to a preset emotional state parameter.

[0081] Here, the preset emotional state parameters are emotional state parameters corresponding to the target position.

[0082] Optionally, the preset emotional state parameters may be emotional state parameters set by a human resources department for a target position.

[0083] Optionally, the preset emotional state parameter can be a second emotional state parameter determined based on the physiological information of the second person in the target game scenario, and the second emotional state parameter is an emotional state parameter corresponding to the second person, and is used to reflect the emotional state of the second person. At this time, the evaluation device 130 can objectively and accurately evaluate the degree of match (degree of tacit understanding) between the first person and the second person based on the first emotional state parameter and the second emotional state parameter, so that the personnel can more accurately and efficiently screen out candidates who share the same ideals or complementary emotions with themselves.

[0084] Exemplarily, when a first person is looking for a second person with stronger sympathy, the second emotional state parameter can be determined based on the second person's physiological information in scenarios such as an elderly person falling down or a child crying, so as to understand the second person's emotional state (whether he or she has sympathy). The first emotional state parameter and the second emotional state parameter can be used to evaluate the degree of tacit understanding between the first person and the second person, so that the first person can accurately and efficiently screen out suitable candidates based on the degree of tacit understanding. If the first person wants to find like-minded people, the higher the degree of tacit understanding, the more the second person meets the first person's screening criteria.

[0085] It is worth mentioning that in order to improve the accuracy of the matching results, the emotional state parameters can be determined multiple times based on the physiological information of the personnel in the same target game scenario to obtain multiple emotional state parameters, and the matching degree between the personnel and the target position can be evaluated based on the average value of the multiple emotional state parameters, or the degree of tacit understanding between personnel can be evaluated based on the average value of the multiple emotional state parameters.

[0086] According to the evaluation method for the degree of matching between personnel and positions provided in the embodiment of the present application, the evaluation device 130 first obtains the physiological information of the personnel in the target game scene, then determines the emotional state parameters through the physiological information, and objectively evaluates the degree of matching between the personnel and the target position based on the emotional state parameters, so that the human resources department can screen out suitable candidates for the position through the matching degree. Compared with the method of determining emotional state parameters through interviews or questionnaires in the prior art, the method of determining emotional state parameters through the physiological information of personnel in the target game scene in the embodiment of the present application is more objective and more efficient, that is, the evaluation method provided by the present application can objectively and efficiently evaluate the degree of matching between personnel and target positions, so that the human resources department can more accurately screen out suitable candidates for the position, and can improve the work efficiency of the human resources department and save labor costs.

[0087] In the embodiment of the present application, the emotional state parameter includes n evaluation parameters, the preset emotional state parameter includes n preset evaluation parameters, the n evaluation parameters correspond one-to-one to the n preset evaluation parameters, and n is an integer greater than or equal to 1.

[0088] As an example but not limitation, evaluating the matching degree between the first person and the target position according to the first emotional state parameter and the preset emotional state parameter can be achieved in the following manner:

[0089] Determine the ratio of each evaluation parameter of the n evaluation parameters to the corresponding preset evaluation parameter to obtain n ratios; and evaluate the matching degree between the first person and the target position according to the n ratios.

[0090] It is worth mentioning that in order to avoid a ratio greater than 1, before determining the ratio of each of the n evaluation parameters to the corresponding preset evaluation parameter to obtain n ratios, the evaluation device 130 will determine whether each of the n evaluation parameters is greater than the corresponding preset evaluation parameter. When the evaluation parameter is greater than the corresponding preset evaluation parameter, an intermediate value is determined, which is the absolute value of the difference between the evaluation parameter and twice the corresponding preset evaluation parameter. The ratio of the intermediate value to the corresponding preset evaluation parameter is determined as the ratio of the evaluation parameter to the corresponding preset evaluation parameter; when the evaluation parameter is less than or equal to the corresponding preset evaluation parameter, the ratio of the evaluation parameter to the corresponding preset evaluation parameter is directly determined as the ratio of the evaluation parameter to the corresponding preset evaluation parameter.

[0091] Exemplarily, when the emotional state parameters include two evaluation parameters, namely, an emotional efficacy value and an emotional arousal value, the evaluation device 130 will first determine whether the emotional efficacy value is greater than a preset emotional efficacy value. If so (the emotional efficacy value is greater than the preset emotional efficacy value), an intermediate value will be determined, and the ratio of the intermediate value to the preset emotional efficacy value will be determined as the ratio of the emotional efficacy value to the preset emotional efficacy value. If not (the emotional efficacy value is less than or equal to the preset emotional efficacy value), the ratio of the emotional efficacy value to the preset emotional efficacy value will be directly determined, and it will be determined whether the emotional arousal value is greater than the preset emotional arousal value. Similarly, if so, an intermediate value will be determined, and the ratio of the intermediate value to the preset emotional arousal value will be determined as the ratio of the emotional arousal value to the preset emotional arousal value. If not, the ratio of the emotional arousal value to the preset emotional arousal value will be directly determined, and then the evaluation device 130 will evaluate the degree of match between the person and the target position based on the two determined ratios. Optionally, the evaluation device 130 determines the degree of matching between the person and the target position according to the adaptation value and a preset threshold, wherein the adaptation value is the sum of each ratio of n ratios multiplied by a corresponding weight value.

[0092] Specifically, the relationship between the adaptation value Y and the ratio X is shown in the following formula:

[0093]

[0094] The emotional state parameters include n evaluation parameters, the preset emotional state parameters include n preset evaluation parameters, the n evaluation parameters correspond to the n preset evaluation parameters one by one, n is an integer greater than or equal to 1, and X i is the ratio of the ith evaluation parameter to the corresponding preset evaluation parameter, A i is the weight of the i-th evaluation parameter.

[0095] For example, if the adaptation value determined based on n ratios is greater than or equal to a preset threshold, the representative person matches the target position. If the adaptation value determined based on n ratios is less than the preset threshold, the representative person does not match the target position.

[0096] For example, the degree of matching between a person and a target position is determined based on the matching value and the mapping relationship between the preset matching value and the matching level.

[0097] Specifically, the evaluation device 130 may first determine a unique preset adaptation value range according to the adaptation value, and then determine the matching degree between the person and the target position according to the mapping relationship between the unique preset adaptation value range and the matching level.

[0098] For example, the mapping relationship may be as shown in Table 1:

[0099] Table 1

[0100] Preset adaptation value / % 0～60 60～70 70～80 80～90 90～100 Matchmaking Level one two three Four five

[0101] As shown in Table 1, the larger the adaptation value, the higher the matching level, and the more the representative person meets the screening criteria (the higher the matching degree).

[0102] For example, when the fitness value determined by the evaluation device 130 is 65%, it can be determined according to Table 1 that the matching level between the person and the target position is level 2, and when the fitness value determined by the evaluation device 130 is 92%, it can be determined according to Table 1 that the matching level between the person and the target position is level 5. At this time, the human resources department can select suitable candidates for the position according to the matching level (for example, recruiting personnel with a matching level of level 5).

[0103] Here, the endpoints of the preset adaptation value range correspond to a greater matching level. For example, an adaptation value of 60% corresponds to a second matching level, and an adaptation value of 70% corresponds to a third matching level.

[0104] Figure 4 is a schematic flow chart of the specific implementation process of the evaluation method provided in the embodiment of the present application. Figure 4 As shown, the evaluation method 400 includes:

[0105] Step S410, obtaining physiological information of the first person in a target game scene, where the target game scene corresponds to a target position and is used to induce emotions of the first person.

[0106] Step S420: determining a first emotional state parameter according to the physiological information.

[0107] Step S430 , determining a ratio of each of the n evaluation parameters to a corresponding preset evaluation parameter to obtain n ratios.

[0108] The emotional state parameters include n evaluation parameters, the preset emotional state parameters include n preset evaluation parameters, the n evaluation parameters correspond one to one with the n preset evaluation parameters, and n is an integer greater than or equal to 1.

[0109] Step S440, evaluating the matching degree between the first person and the target position according to the n ratios.

[0110] Optionally, the evaluation device 130 determines the degree of matching between the person and the target position according to the adaptation value and a preset threshold, wherein the adaptation value is the sum of each ratio of n ratios multiplied by a corresponding weight value.

[0111] For example, the degree of matching between a person and a target position is determined based on the matching value and the mapping relationship between the preset matching value and the matching level.

[0112] Here, step S410 is implemented in the same way as step S310, and step S420 is implemented in the same way as step S320, and will not be repeated here. Steps S430 and S440 are sub-steps of step S330, which is a possible implementation method of evaluating the degree of match between personnel and target positions based on emotional state parameters.

[0113] In the embodiment of the present application, the more evaluation parameters the emotional state parameter includes, the more accurate the result of the matching degree evaluated by the evaluation device 130 according to the emotional state parameter.

[0114] Exemplarily, the target position is a special forces soldier, and the target game scene is a terrorist attack scene. After the evaluation device 130 obtains the physiological information of the personnel in the target game scene, if the emotional state parameters determined according to the physiological information include two evaluation parameters, namely, the emotional efficacy value and the emotional arousal value, then at this time, the ratio of these two evaluation parameters to the corresponding preset evaluation parameters can only be used to understand the degree of fear reaction of the personnel in the face of the terrorist attack scene. If the emotional state parameters determined according to the physiological information include six evaluation parameters, namely, the emotional efficacy value, the emotional arousal value, the peak value of the emotional efficacy value, the peak value of the emotional arousal value, the recovery time of the emotional efficacy value, and the recovery time of the emotional arousal value, then at this time, the fluctuation degree of the fear reaction of the personnel can also be understood through the ratio of the two evaluation parameters, namely, the peak value of the emotional efficacy value and the peak value of the emotional arousal value, to the corresponding preset evaluation parameters, and the ratio of the two evaluation parameters, namely, the recovery time of the emotional efficacy value and the recovery time of the emotional arousal value, to the corresponding preset evaluation parameters, can be used to understand the personnel's ability to cope with terrorist attack scenes (such as whether they can quickly concentrate on finding the source of threat under time pressure), thereby enabling a more comprehensive evaluation of the degree of match between the personnel and the target position.

[0115] Here, when multiple emotion valence values ​​are determined based on physiological information, the ratio of the average value of the multiple emotion valence values ​​to the preset emotion valence value is used as the evaluation criterion. Similarly, when multiple emotion arousal values ​​are determined based on physiological information, the ratio of the average value of the multiple emotion arousal values ​​to the preset emotion arousal value is used as the evaluation criterion.

[0116] The recovery time of the emotional efficacy value is the time difference between the peak value and the baseline value among multiple emotional efficacy values, that is, the time it takes for a person to recover from an emotionally fluctuating state to an emotionally calm state. The recovery time of the emotional arousal value is the time difference between the peak value and the baseline value among multiple emotional arousal values, that is, the time it takes for a person to recover from an emotionally fluctuating state to an emotionally calm state.

[0117] For example, the recovery time of the emotional effectiveness value can be 2s, 5s, 30s, etc., and the recovery time of the emotional arousal value can be 3s, 8s, 30s, etc.

[0118] When there are multiple peaks in the multiple emotional efficacy values, the maximum value among the absolute values ​​of the multiple peaks is selected, and the ratio of the maximum value to the peak value of the preset emotional efficacy value is used as the evaluation standard, and the time difference between the maximum value and the reference value is used as the recovery time of the emotional efficacy value. Similarly, when there are multiple peaks in the multiple emotional arousal values, the maximum value among the absolute values ​​of the multiple peaks is selected, and the ratio of the maximum value to the peak value of the preset emotional arousal value is used as the evaluation standard, and the time difference between the maximum value and the reference value is used as the recovery time of the emotional arousal value.

[0119] Figure 5 is a schematic block diagram of an evaluation method provided by another embodiment of the present application, such as Figure 5 As shown, the evaluation method 500 may include:

[0120] Step S510, determining the object of interest of the first person according to the eye movement information of the first person in a preset game scene.

[0121] For example, the preset game scene includes items related to various positions, and the evaluation device 130 determines the item on which the person's eyes stay the longest as the object of interest.

[0122] Step S520, determining a target position according to the object of interest.

[0123] For example, if the person is interested in advanced technology and scientific issues, the target position can be determined as a scientist, if the person is interested in regulations and clauses, the target position can be determined as a lawyer, and if the person is interested in numbers, the target position can be determined as an accountant.

[0124] Step S530, determining the target game scene according to the target position.

[0125] For example, when the target position is a kindergarten teacher, the target game scene can be determined as a scene of a child crying; when the target position is a firefighter, the target game scene can be determined as a fire scene.

[0126] Step S540, obtaining physiological information of the first person in a target game scene, where the target game scene corresponds to the target position and is used to induce emotions of the first person.

[0127] Among them, the implementation method of step S540 is the same as that of the above-mentioned step S310, which will not be repeated here.

[0128] Step S550: determining a first emotional state parameter according to the physiological information.

[0129] Among them, the implementation method of step S550 is the same as that of the above-mentioned step S320, which will not be repeated here.

[0130] Step S560: evaluating the matching degree between the first person and the target position according to the first emotional state parameter.

[0131] Among them, the implementation method of step S560 is the same as that of the above-mentioned step S330, which will not be repeated here.

[0132] The embodiment of the present application provides an evaluation method for the degree of match between personnel and positions. The evaluation device 130 first determines the target position through the object of interest. After determining the target game scene through the target position, the emotional state parameters are further determined according to the physiological information of the personnel in the target game scene, and the degree of match between the personnel and the target position is objectively and accurately evaluated based on the emotional state parameters, so that the human resources department can more efficiently and accurately screen out suitable candidates for the target position from the personnel who are interested in the target position.

[0133] Here, physiological information may also include eye movement information, through which one can understand a person's ability to cope with a target game scenario.

[0134] For example, if the target position is a special forces soldier and the target game scene is a terrorist attack scene, the speed at which the first person discovers the threat source can be understood through eye movement information.

[0135] Figure 6 600 is a schematic block diagram of an evaluation device provided in an embodiment of the present application. The evaluation device 600 may be a server, or a chip or circuit disposed in the server, such as Figure 6 As shown, the evaluation device 600 includes an acquisition module 610 , a determination module 620 and an evaluation module 630 .

[0136] Among them, the acquisition module 610 is used to obtain the physiological information of the first person in the target game scene (such as heart rate information, heart rate variability information, facial expression information and micro-expression information, etc.), the target game scene corresponds to the target position (such as waiter, nurse, teacher, firefighter, special forces, civil servant, etc.), and is used to induce the emotions of the first person (such as happiness, anger, missing, sadness, fear and surprise, etc.). The determination module 620 is used to determine the first emotional state parameter according to the physiological information. The evaluation module 630 is used to evaluate the matching degree between the first person and the target position according to the first emotional state parameter.

[0137] Optionally, the evaluation module 630 is specifically configured to evaluate the degree of matching between the first person and the target position according to the first emotional state parameter and a preset emotional state parameter.

[0138] Optionally, the first emotional state parameter includes n evaluation parameters, the preset emotional state parameter includes n preset evaluation parameters, the n evaluation parameters correspond one-to-one to the n preset evaluation parameters, and n is an integer greater than or equal to 1; the evaluation module 630 is specifically used to determine the ratio of each of the n evaluation parameters to the corresponding preset evaluation parameter to obtain n ratios; and evaluate the degree of match between the first person and the target position based on the n ratios.

[0139] Optionally, the evaluation module 630 is specifically used to determine the degree of matching between the first person and the target position according to the adaptation value and a preset threshold, wherein the adaptation value is the sum of each ratio of n ratios multiplied by a corresponding weight value.

[0140] Optionally, the preset emotional state parameter is a second emotional state parameter determined based on physiological information of the second person in the target game scenario.

[0141] Optionally, the determination module 620 is further used to determine the object of interest of the first person according to the eye movement information of the first person in a preset game scene; determine the target position according to the object of interest; and determine the target game scene according to the target position.

[0142] Optionally, the determination module 620 is specifically used to input the physiological information into a pre-trained deep learning model, and determine the first emotional state parameter according to an output value of the deep learning model.

[0143] Optionally, the first emotional state parameter includes at least one of the following evaluation parameters: emotional efficacy value, emotional arousal value, peak value of emotional efficacy value, peak value of emotional arousal value, recovery time of emotional efficacy value and recovery time of emotional arousal value.

[0144] Optionally, the physiological information includes at least one of the following information: facial expression information, micro-expression information, heart rate information, heart rate variability information, skin resistance information and brain wave information.

[0145] Figure 7 700 is a schematic diagram of the structure of the evaluation device provided in the embodiment of the present application. The evaluation device 700 may be a server, or a chip or circuit disposed in the server. Figure 7 As shown, the evaluation device 700 includes: a processor 710, a memory 720 and a communication interface 730. The memory 720 stores instructions, and the processor 710 is used to execute the instructions in the memory 720. When the instructions are executed, the processor 710 is used to execute the evaluation method provided by the above method embodiment, and the processor 710 is also used to control the communication interface 730 to communicate with the outside world.

[0146] Furthermore, the processor 710, the memory 720 and the communication interface 730 may communicate with each other through internal connection paths to transfer control and / or data signals.

[0147] Furthermore, the memory 720 may be integrated into the processor 710 or may be provided separately from the processor 710 .

[0148] Specifically, the evaluation device 700 can be used to perform Figure 3 In each step of the evaluation method 300, the evaluation device 700 may include a Figure 3 Furthermore, each module in the evaluation device 700 and the above-mentioned other operations and / or functions are respectively for realizing Figure 3 The specific process of each module executing the above corresponding steps has been described in detail in the evaluation method 300, and will not be repeated here for the sake of brevity.

[0149] The embodiment of the present application further provides an evaluation system 100 , which includes a display device 110 , a collection device 120 , and an evaluation device 130 provided by any of the aforementioned embodiments, wherein the evaluation device 130 is in communication connection with the collection device 120 .

[0150] Among them, the display device 110 is used to display the game scene, the collection device 120 is used to collect physiological information of the personnel, and the evaluation device 130 is used to determine the emotional state parameters according to the acquired physiological information, and evaluate the matching degree between the personnel and the target position according to the emotional state parameters.

[0151] Specifically, the evaluation device 130 sends a message to the receiver's terminal 140 that contains the degree of matching between the person and the target position, and the message may also contain information on the emotional state parameters.

[0152] The recipient may be a person or a human resources department, etc., and the terminal 140 may be a terminal device such as a mobile phone, a tablet computer, a smart watch, a smart headset, etc., but is not limited thereto.

[0153] An embodiment of the present application also provides a computer-readable storage medium, which includes a computer program. When the computer-readable storage medium is run on a computer, the computer executes the evaluation method provided in the above evaluation method embodiment.

[0154] An embodiment of the present application also provides a computer program product comprising instructions, and when the computer program product is run on a computer, the computer is enabled to execute the evaluation method provided in the above evaluation method embodiment.

[0155] 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 gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0156] It should also be understood that the memory 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. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0157] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or 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 can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0158] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0159] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0160] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0161] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0162] If the functions are implemented in the form of software functional units and sold or used as independent products, they 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. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods 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 magnetic disk or an optical disk.

[0163] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present 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. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for evaluating the degree of matching between personnel and positions, characterized in that: include: Acquiring physiological information of a first person in a target game scene, wherein the target game scene corresponds to a target position and is used to induce emotions of the first person; wherein the game scene is a simulation of various scenes related to joy, anger, sorrow, happiness, and fear in work or life; and the physiological information includes at least one of the following information: facial expression information, heart rate information, heart rate variability information, skin resistance information, and brain wave information; Determine a first emotional state parameter according to the physiological information; wherein the first emotional state parameter includes at least one of the following evaluation parameters: an emotional potency value, an emotional arousal value, a peak value of the emotional potency value, a peak value of the emotional arousal value, a recovery time of the emotional potency value, and a recovery time of the emotional arousal value; evaluating the degree of match between the first person and the target position according to the first emotional state parameter; The step of evaluating the matching degree between the first person and the target position according to the first emotional state parameter includes: Evaluating the degree of matching between the first person and the target position according to the first emotional state parameter and a preset emotional state parameter; The first emotional state parameter includes n evaluation parameters, the preset emotional state parameter includes n preset evaluation parameters, the n evaluation parameters correspond one to one with the n preset evaluation parameters, and n is an integer greater than 1; The evaluating the matching degree between the first person and the target position according to the first emotional state parameter and a preset emotional state parameter includes: Determining a ratio of each of the n evaluation parameters to a corresponding preset evaluation parameter to obtain n ratios; Evaluating the matching degree between the first person and the target position according to the n ratios; The evaluating the matching degree between the first person and the target position according to the n ratios includes: The degree of matching between the first person and the target position is determined according to the adaptation value and a preset threshold, wherein the adaptation value is the sum of each of the n ratios multiplied by the corresponding weight value.

2. The evaluation method according to claim 1, characterized in that: The preset emotional state parameter is a second emotional state parameter determined based on the physiological information of the second person in the target game scene.

3. The evaluation method according to claim 1 or 2, characterized in that: Before obtaining the physiological information of the first person in the target game scene, the evaluation method further includes: Determining an object of interest to the first person according to eye movement information of the first person in a preset game scene; Determine the target position according to the interested object; The target game scene is determined according to the target position.

4. The evaluation method according to claim 1, characterized in that: The determining of the first emotional state parameter according to the physiological information includes: The physiological information is input into a pre-trained deep learning model, and the first emotional state parameter is determined according to an output value of the deep learning model.

5. A device for evaluating the degree of matching between personnel and positions, characterized in that: include: an acquisition module, used to acquire physiological information of the first person in a target game scene, the target game scene corresponds to a target position, and is used to induce the emotions of the first person; wherein the game scene is a simulation of various scenes related to joy, anger, sorrow, happiness, and fear in work or life; the physiological information includes at least one of the following information: facial expression information, heart rate information, heart rate variability information, skin resistance information, and brain wave information; a determination module, configured to determine a first emotional state parameter according to the physiological information; wherein the first emotional state parameter includes at least one of the following evaluation parameters: an emotional efficacy value, an emotional arousal value, a peak value of the emotional efficacy value, a peak value of the emotional arousal value, a recovery time of the emotional efficacy value, and a recovery time of the emotional arousal value; An evaluation module, configured to evaluate the degree of matching between the first person and the target position according to the first emotional state parameter; The evaluation module is specifically used to: evaluate the matching degree between the first person and the target position according to the first emotional state parameter and a preset emotional state parameter; The first emotional state parameter includes n evaluation parameters, the preset emotional state parameter includes n preset evaluation parameters, the n evaluation parameters correspond one to one with the n preset evaluation parameters, and n is an integer greater than 1; The evaluating the matching degree between the first person and the target position according to the first emotional state parameter and a preset emotional state parameter includes: Determining a ratio of each of the n evaluation parameters to a corresponding preset evaluation parameter to obtain n ratios; Evaluating the matching degree between the first person and the target position according to the n ratios; The evaluation module is specifically used to determine the matching degree between the first person and the target position according to the adaptation value and a preset threshold, wherein the adaptation value is the sum of each ratio of the n ratios multiplied by the corresponding weight value.

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