JP6288748B1 - Evaluation support system and evaluation support apparatus - Google Patents

Abstract

An evaluation support system and an evaluation support apparatus capable of quantitatively evaluating the contents of a presentation of a proposer are provided. An evaluation support system 100 for evaluating the content of a presentation of a proposer via a user-limited network 4 that obtains target information D generated based on the video of the presentation of the proposer. Means S110, past target information acquired in advance, reference information used for evaluation of the past target information, and three or more levels of association between the past target information and the reference information are stored. A reference database that has been processed, evaluation means S120 that refers to the reference database, obtains evaluation information including first relations of three or more stages between the target information D and the reference information, and the evaluation information Output means S130 that generates an evaluation result R based on the result and transmits the evaluation result R to the terminal 2 owned by the proposer. That. [Selection] Figure 1

Description

  The present invention relates to an evaluation support system and an evaluation support apparatus for evaluating the contents of a presentation of a proposer.

  2. Description of the Related Art In recent years, services on the Internet have been actively developed, for example, based on the social trust of users (proposers), which can promote the enjoyment of services among individuals. For example, services that issue virtual stocks based on the social trust of the proposer and other users buy and sell virtual stocks are attracting attention. In such a field, the social trust of the proposer is evaluated by the degree of attention to the proposer in other social networking services (SNS: Social Networking Service), such as Twitter (registered trademark) and Facebook (registered trademark). It is evaluated by the number of followers.

  On the other hand, when issuing a virtual stock or the like based on the proposer, a user who buys or sells the virtual stock or the like considers buying or selling of the virtual stock or the like mainly based on the idea including the future potential of the proposer. For this reason, for example, when the degree of attention to the proposer in other social networking services is high, even if the idea of the proposer is skeptical, the social credibility of the proposer may be appreciated more than necessary. There is. In addition, in the proposer who does not use other social networking services, even if the idea is promising, the social trust of the proposer may be evaluated low. For this reason, it is difficult for the conventional evaluation method to appropriately evaluate the social credibility of the proposer.

  As a method for appropriately evaluating the social trust of the proposer, there is a method for evaluating a presentation including the idea of the proposer. However, it is necessary for an operator or the like to spend enormous amounts of time and labor costs of the evaluator in order to evaluate each proposer's presentation. Moreover, since it is assumed that the evaluation dispersion | variation for every evaluator will also become large, quantitative evaluation is mentioned as a subject.

  In this regard, in order to evaluate the presentation of the proposer, for example, a presentation evaluation apparatus disclosed in Patent Document 1 has been proposed.

  The presentation evaluation apparatus disclosed in Patent Document 1 displays a slide when a presentation is started. Then, the evaluation of the line of sight detected by the line-of-sight direction detection device is added. Then, this apparatus checks the timing of turning each page. Based on this result, the page turning timing is compared with the time extracted from the agenda. As a result, when a large deviation occurs, a warning indicating that effect is displayed on the presentation screen. For example, if the next page has been advanced earlier than the scheduled time, “Proceeded early (X seconds)” is displayed.

JP 2007-219161 A

  However, with the disclosed technique of Patent Document 1, it is only possible to evaluate based on how long a lecture was spent on the presentation material, and the content of the presentation cannot be evaluated. Under such circumstances, it is desired to be able to quantitatively evaluate the content of the proposer's presentation.

  Therefore, the present invention has been devised in view of the above-described problems, and an object of the present invention is to provide an evaluation support system and an evaluation support apparatus that can quantitatively evaluate the content of the presentation of the proposer. It is in.

  An evaluation support system according to a first aspect of the present invention is an evaluation support system that evaluates the content of a presentation of a proposer via a user-limited network, and includes target information generated based on the video of the presentation of the proposer. Acquiring means for acquiring, past target information acquired in advance, reference information used for evaluation of the past target information, and a degree of association of three or more levels between the past target information and the reference information Is stored in a reference database, evaluation means for referring to the reference database, obtaining evaluation information including first relations of three or more stages between the target information and the reference information, and the evaluation information Output means for generating an evaluation result based on the result and transmitting the evaluation result to a terminal held by the proposer.

  The evaluation support system according to a second invention is characterized in that, in the first invention, the evaluation result includes a first evaluation selected from two or more preset evaluation criteria.

  In the evaluation support system according to a third invention, in the first invention or the second invention, the output means includes transmitting the video of the presentation of the proposer and the evaluation result to another user terminal. Features.

  The evaluation support system according to a fourth aspect of the present invention is characterized in that, in any one of the first to third aspects, the presentation of the proposer includes a corporate advertisement.

  In the evaluation support system according to a fifth aspect of the present invention, in any one of the first to fourth aspects, the target information is information excluding a person's video.

  The evaluation support system according to a sixth aspect of the present invention is the evaluation system according to any one of the first to fifth aspects, wherein the target information includes an action of the proposer.

  The evaluation support system according to a seventh aspect of the present invention is the evaluation support system according to any one of the first to sixth aspects, wherein the acquisition means generates the target information based on a video of the suggestor's presentation in 5 seconds to 1 minute It is characterized by acquiring.

  In any one of the first to seventh inventions, the evaluation support system according to an eighth aspect of the present invention is configured such that when the relationship between the past target information and the reference information is newly acquired, the relationship is It is further characterized by further comprising updating means for reflecting the association degree.

  An evaluation support apparatus according to a ninth aspect of the present invention is an evaluation support apparatus for evaluating the contents of a presentation of a proposer registered in a user-limited network, and the target information generated based on the video of the presentation of the proposer Three or more levels of association between the past target information acquired in advance, the reference information used in the evaluation of the past target information, and the past target information and the reference information A reference database in which the degree is stored, an evaluation unit that refers to the reference database, obtains evaluation information including first relations of three or more stages between the target information and the reference information, and the evaluation information And an output unit for generating an evaluation result based on the above and outputting the evaluation result.

  According to 1st invention-8th invention, an evaluation means refers to a reference database, and acquires the evaluation information containing the 1st relevance between object information and reference information. The target information is generated based on the video of the proposer's presentation. For this reason, a quantitative evaluation result can be acquired with respect to the contents of the presentation of the proposer. Thereby, it becomes possible to connect the quantitative evaluation result to the social credibility of the proposer.

  In particular, according to the second invention, the evaluation result includes a first evaluation selected from two or more preset evaluation criteria. Therefore, it is possible to output an evaluation result based on a common evaluation criterion even for presentations in different fields. This makes it possible to obtain quantitative evaluation results for presentations in various fields.

  In particular, according to the third invention, the output means includes transmitting the video of the proposer's presentation and the evaluation result to another user terminal. For this reason, for example, when another user holding another user terminal conducts a public call for presentations, quantitative selection support can be performed via the evaluation support system. As a result, it is possible to reduce the variation in examination criteria caused by the selection person, and it is possible to reduce labor costs and selection time spent for selection.

  In particular, according to the seventh invention, the acquisition means acquires the target information generated based on the video of the presentation of the proposer in the range of 5 seconds to 1 minute. For this reason, it is possible to easily obtain a quantitative evaluation result while suppressing an increase in data.

  In particular, according to the eighth aspect, when the update unit newly acquires the relationship between the past target information and the reference information, the update unit reflects the relationship in the association degree. For this reason, the association degree can be easily updated, and the accuracy of the evaluation result can be further increased.

  According to the ninth aspect, the evaluation unit refers to the reference database, and acquires evaluation information including the first association degree between the target information and the reference information. The target information is generated based on the video of the proposer's presentation. For this reason, a quantitative evaluation result can be acquired with respect to the contents of the presentation of the proposer. Thereby, it becomes possible to connect the quantitative evaluation result to the social credibility of the proposer.

It is a mimetic diagram showing the example of composition of the evaluation support system in an embodiment. FIG. 2A is a schematic diagram illustrating an example of the target information, and FIG. 2B is a schematic diagram illustrating an example of the evaluation result. FIG. 3A is a schematic diagram illustrating an example of a configuration of the evaluation support apparatus in the embodiment, and FIG. 3B is a schematic diagram illustrating an example of a function of the evaluation support apparatus in the embodiment. FIG. 4 is a schematic diagram illustrating an example of a reference database according to the embodiment. FIG. 5 is a schematic diagram illustrating a first modification of the reference database according to the embodiment. FIG. 6 is a schematic diagram illustrating a second modification of the reference database according to the embodiment. FIG. 7 is a schematic diagram illustrating an example of question information and answer information. FIG. 8 is a schematic diagram illustrating an example of a question database according to the embodiment. FIG. 9 is a flowchart illustrating an example of the operation of the evaluation support system in the embodiment. FIG. 10 is a flowchart illustrating a first modification of the operation of the evaluation support system in the embodiment. FIG. 11 is a flowchart illustrating a second modification of the operation of the evaluation support system in the embodiment. FIG. 12 is a schematic diagram illustrating a modified example of the question database according to the embodiment.

  Hereinafter, an example of an evaluation support system according to an embodiment of the present invention will be described with reference to the drawings.

(Embodiment: Configuration of Evaluation Support System 100)
With reference to FIG. 1, an example of a configuration of an evaluation support system 100 in the embodiment will be described. FIG. 1 is a block diagram showing the overall configuration of the evaluation support system 100 in the present embodiment.

  As shown in FIG. 1, the evaluation support system 100 includes an evaluation support apparatus 1. The evaluation support apparatus 1 may be connected to, for example, the server 3 or the like in addition to being connected to the user terminal 2 via the public communication network 4 (network), for example.

  The evaluation support system 100 is mainly used for developing services on the Internet limited to users (services for membership registration). The evaluation support system 100 can output a quantitative evaluation result R for the target information D generated based on the video of the presentation of the user (proposer). Therefore, the administrator or the like of the evaluation support system 100 can consider the social credit of the proposer based on the evaluation result R, for example, and can set virtual stocks or the like according to the social credit. In addition, the proposer can consider improving the presentation based on the evaluation result R, for example. Further, the target information D and the evaluation result R need not be disclosed on the Internet. For this reason, it is possible to evaluate the contents of the presentation of the proposer in an unknown state. Further, the evaluation support system 100 transmits the evaluation result R to the user terminal 2 owned by the proposer. For this reason, the proposer can grasp the quantitative evaluation for the presentation.

  Note that the evaluation support system 100 can transmit the video of the presentation of the proposer and the evaluation result R to another user terminal owned by another user. For this reason, when another user conducts an open call for presentations, etc., quantitative selection support can be performed via the evaluation support system 100.

<Evaluation support apparatus 1>
The evaluation support apparatus 1 in this embodiment is mainly used by an administrator of the evaluation support system 100 or the like. The evaluation support apparatus 1 acquires the target information D and outputs an evaluation result R for the target information D. Other users, managers, and the like can examine, for example, the social credibility of the proposer and the video quality of the presentation based on the evaluation result R obtained by the evaluation support apparatus 1.

  The evaluation support apparatus 1 acquires the target information D generated by the user terminal 2 from the user terminal 2 as shown in FIG. The target information D is generated based on the video of the suggestor's presentation using the camera and microphone of the user terminal 2. The target information D includes, for example, at least one of presentation data P, audio data S, and facial expression data F. The evaluation support apparatus 1 extracts presentation data P and the like from the acquired target information D as necessary.

  The presentation data P includes, for example, at least one of content data relating to the content of the material used for the presentation by the proposer and progress data relating to how the proposer proceeds with the presentation. The content data may include data obtained by converting the content of the material into text data, and may include image data such as a figure or a graph. The progress data includes data related to the progress time for explaining each material and the progress time of the entire presentation. The progress data includes, for example, data related to the order in which materials are used.

  The voice data S includes, for example, at least one of speech data related to the speech of the proposer and tone data related to the tone of the proposer. The utterance data includes, for example, data obtained by converting the utterance of the proposer into text data. The tone data includes, for example, data related to the speed of the utterance of the proposer, the volume of voice, intonation, time between utterances, and the like.

  The facial expression data F includes, for example, at least one of first facial expression data regarding the characteristics of the eyes of the proposer and facial data regarding the characteristics of the entire face of the proposer. The first facial expression data includes data relating to features such as the eyes of the proposer, eyesight, and line of sight. The face data includes data relating to body characteristics such as the face color, wrinkles, hair, mouth, and nose of the proposer.

  For example, as illustrated in FIG. 2B, the evaluation support apparatus 1 generates an evaluation result R for the target evaluation D and outputs the evaluation result R to the user terminal 2. The evaluation result R has, for example, at least one of planability, sustainability, future potential, presentation ability, estimated health value, estimated age, and evaluation price. In addition to generating a score for each item, the evaluation result R may generate a comment.

  The evaluation result R is, for example, an evaluation (first evaluation) selected from the evaluation standards using at least one of planability, sustainability, future potential, presentation ability, estimated health value, estimated age, and evaluation price as an evaluation standard. May be included. In this case, the evaluation criteria can be set in advance in two or more levels, and can be set in a score format such as 101 levels from 0 to 100 points, for example. In FIG. 2B, the first evaluation “XX point” in the evaluation criterion “planning” is displayed. The evaluation result R may generate a comment in addition to generating a score corresponding to each evaluation criterion.

  Regarding planability, sustainability, and future potential, the evaluation (for example, evaluation criteria) of the proposal content of the proposer is mainly shown. The planability can be used, for example, for evaluation of plan omissions and omissions in the proposal of the proposer. Sustainability can be used, for example, for evaluating whether or not the proposal can be realized in a proposal. The future can be used, for example, for objective future evaluation in the proposal of the proposer.

  Among the reference information, the presentation ability, the estimated health value, and the estimated age indicate an evaluation (e.g., evaluation criteria) for the proposer itself. The presentation ability can be used, for example, for evaluating the proposal progress and explanation method of the proposer. The estimated health value can be used to evaluate the health condition obtained from the appearance of the proposer. The estimated age can be used to evaluate the estimated age obtained from the appearance of the proposer, for example.

  FIG. 3A is a schematic diagram illustrating an example of the configuration of the evaluation support apparatus 1. As the evaluation support apparatus 1, an electronic device such as a personal computer (PC) is used. The evaluation support apparatus 1 includes a housing 10, a CPU 101, a ROM 102, a RAM 103, a storage unit 104, and I / Fs 105 to 107. Each component 101 to 107 is connected by an internal bus 110.

  A CPU (Central Processing Unit) 101 controls the entire evaluation support apparatus 1. A ROM (Read Only Memory) 102 stores an operation code of the CPU 101. A RAM (Random Access Memory) 103 is a work area used when the CPU 101 operates. The storage unit 104 stores various information such as the target information D. As the storage unit 104, for example, an HDD (Hard Disk Drive), a data storage device such as an SSD (Solid State Drive) or a floppy disk is used. For example, the evaluation support apparatus 1 may include a GPU (Graphics Processing Unit) (not shown). By having a GPU, it is possible to perform higher-speed arithmetic processing than usual.

  The I / F 105 is an interface for transmitting and receiving various types of information to and from the user terminal 2 via the public communication network 4. The I / F 106 is an interface for transmitting / receiving information to / from the input unit 108. For example, a keyboard is used as the input part 108, and an administrator of the evaluation support system 100 inputs various information or a control command of the evaluation support apparatus 1 through the input part 108. The I / F 107 is an interface for performing transmission / reception of various information with the output unit 109. The output part 109 outputs various information stored in the storage unit 104 or the processing status of the evaluation support apparatus 1. A display is used as the output portion 109, and for example, a touch panel type may be used.

  FIG. 3B is a schematic diagram illustrating an example of functions of the evaluation support apparatus 1. The evaluation support apparatus 1 includes an acquisition unit 11, an evaluation unit 12, an output unit 14, an input unit 15, and an information DB 16. The evaluation support apparatus 1 may include an update unit 13, for example. Note that the function shown in FIG. 3B is realized by the CPU 101 executing a program stored in the storage unit 104 or the like using the RAM 103 as a work area. Moreover, each structure 11-16 may be controlled by artificial intelligence, for example. Here, “artificial intelligence” may be based on any known artificial intelligence technology.

<Information DB16>
The information DB 16 includes a reference database in which past target information acquired in advance and reference information used for evaluation of past target information are stored. In addition to storing evaluation information obtained by evaluating the target information D, the information DB 16 includes, for example, a database in which various types of information such as a format for displaying the evaluation result R based on the evaluation information and evaluation criteria are stored. The reference database and the database are stored in the storage unit 104 realized by an HDD, an SSD, or the like. Each structure 11-15 memorize | stores various information in information DB16 as needed, or takes out various information.

  In the reference database, for example, as shown in FIG. 4, three or more levels of association between past target information and reference information are stored. The past target information and reference information have a plurality of data, and are linked with the association degree indicating the degree of the relationship, for example, the degree of relevance of three or more levels such as 10 levels and 5 levels (in FIG. Displayed with line features). For example, “content A” included in past content data indicates an association degree “80%” with “plan A” included in the planability of the reference information, and “sustainability” included in the sustainability of the reference information. The degree of association with “A” is “10%”.

  The reference database has, for example, an algorithm that can calculate the association degree. As the reference database, for example, a function (classifier) optimized based on past target information, reference information, and association degree may be used.

  The past target information includes data corresponding to the target information D described above, and includes, for example, at least one of past presentation data, past audio data, and past facial expression data. Since the characteristics of each data are the same as each data which the target information D mentioned above has, the description is omitted.

  The reference information includes data corresponding to the evaluation result R, and includes at least one of planability, sustainability, future potential, presentation ability, estimated health value, estimated age, and evaluation price, for example. As reference information, a result obtained by evaluating past target information is used. Since the characteristics of each data are the same as each data which the evaluation result R mentioned above has, the description is omitted.

  Since the reference information has the data as described above, an evaluation result R for the presentation of the proposer can be generated. Each of the above data is an example, and can be arbitrarily set as necessary.

  The past target information and reference information may be stored in the reference database in a video or sound data format, for example, or may be stored in a data format such as a numerical value, a matrix (vector), or a histogram.

  The association degree is calculated based on the relationship between past target information and reference information. The association degree is calculated using, for example, machine learning. For example, deep learning is used for machine learning. For example, as data used as past presentation data, past voice data, and past facial expression data, data processed in advance by machine learning or the like may be used. That is, a result of machine learning of past target information acquired in advance for each data may be used as past presentation data, past voice data, and past facial expression data.

  For example, as shown in FIG. 5, the association degree may be calculated based on a relationship between a combination of two or more data included in past target information and reference information. For example, a combination of “content A” included in past content data of past target information and “progress B” included in past progress data is between “plan A” included in the planability of the reference information. The degree of association is “80%”, and the degree of association with “plan B” is “10%”. In this case, when generating the evaluation result R, it is possible to improve accuracy and expand the range of options.

  The past target information may include intermediate information associated with each piece of data and reference information included in the past target information, for example, as shown in FIG. In this case, the intermediate information is associated with at least one of past presentation data, past audio data, and past facial expression data through three or more levels of similarity, and is associated with reference information through association. ing. Thereby, even when at least one of past presentation data, past voice data, and past facial expression data is updated, added, etc., it is not necessary to update the association degree. As a result, it is possible to significantly reduce the time spent for reconstructing the reference database associated with the change of the evaluation object.

<Acquisition unit 11>
The acquisition unit 11 acquires the target information D. In addition to acquiring the target information D from the user terminal 2, the acquisition unit 11 may acquire the target information D from a storage medium such as a portable memory. Note that the data format of the target information D is arbitrary. For example, the acquisition unit 11 may convert the data into an arbitrary data format.

  The acquisition unit 11 may extract only specific data included in the target information D, for example, and extracts at least one of content data, progress data, audio data S, and facial expression data F, for example. Data to be extracted can be arbitrarily set by an administrator or the like.

<Question part 11a>
The acquisition unit 11 includes, for example, a question unit 11a. The question unit 11 a generates question information Q for the proposer based on the target information D, and outputs the question information Q to the user terminal 2 or the like via the output unit 14. The user terminal 2 or the like displays the acquired question information Q, for example, as shown in FIG. In addition to generating and outputting the question information Q in the text data format, the question unit 11a may generate and output the question information Q in the voice data format, for example. The question unit 11a may generate and output the question information Q during the acquisition of the target information D (for example, during the presentation of the proposer), for example, after acquiring the target information D (for example, the target person's presentation) The question information Q may be generated and output after the presentation). The number of times the question unit 11a generates and outputs the question information Q is arbitrary.

  The question unit 11a generates the question information Q with reference to, for example, a question database. The question database has past target information acquired in advance and past question information used for questions of past target information, and is stored in the information DB 16. The question database may store, for example, stored character strings such as morphemes, and the question unit 11a may generate the question information Q by combining the character strings stored in the question database. In this case, the question unit 11a may generate the question information Q based on, for example, the similarity between the target information D and the past target information, for example, in addition to referring to a question sentence published on the Internet. .

  For example, as shown in FIG. 8, the question database stores three or more levels of question relations between past target information and past question information. The past target information and the past question information are linked by the question relation indicating the degree of the relationship, for example, the degree of relevance of three or more levels such as 10 levels or 5 levels (in FIG. Display). For example, “content A” included in past content data indicates a question association degree “60%” with “question A” included in past question information, and question association with “question C”. Degree indicates “30%”. For example, the question unit 11a generates and outputs past question information having the highest degree of question association as question information Q. In addition, when the question part 11a produces | generates the question information Q, it can set so that the question relevance degree in arbitrary threshold values or ranges may be referred.

  The question database has, for example, an algorithm that can calculate the question association degree. As the question database, for example, functions (classifiers) optimized based on past target information, past question information, and question relations may be used.

  The past target information and the past question information are stored in the question database in a text format, for example, and may be stored in a data format such as a numerical value, a matrix (vector), or a histogram.

  The question association degree is calculated based on the relationship between past target information and past question information. The question association degree is calculated using, for example, machine learning. For example, deep learning is used for machine learning. In the question database, as in the reference database shown in FIG. 5, the question association degree may be calculated based on a combination of two or more data included in past target information.

<Addition part 11b>
The acquisition unit 11 includes, for example, an addition unit 11b. The adding unit 11b acquires answer information A based on the answer of the proposer with respect to the question information Q. For example, as shown in FIG. 7, the answer information A is generated based on the content that the proposer has answered to the question information Q displayed on the user terminal 2.

  In addition to extracting the response information A from the acquired target information D, the adding unit 11b may acquire the response information A as information different from the target information D, for example. The adding unit 11b may acquire the response information A in the text data format, or may acquire the response information A in the audio data format, for example. After the adding unit 11b acquires the answer information A, for example, the question unit 11a may generate the question information Q for the proposer again based on the answer information A. For example, the adding unit 11b may acquire the answer information A as a part of the target information D, and may classify the answer information A into any one of the presentation data P, the voice data S, and the facial expression data F, for example. When the adding unit 11b acquires the answer information A as information different from the target information D, the reference database includes past answer information corresponding to the answer information A.

  In addition to the target information D, the acquisition unit 11 may acquire, for example, personal information regarding the target person stored in the target information D. Thereby, it becomes possible to output the evaluation result R corresponding to the person information.

<Evaluation unit 12>
The evaluation unit 12 acquires evaluation information including the first association degree of three or more stages between the target information D and the reference information. The evaluation unit 12 refers to the reference database stored in the storage unit 104, selects past target information that matches or is similar to the target information D, and determines the association degree associated with the selected past interview data. Calculated as the first degree of association. In addition, the evaluation unit 12 may calculate the first association degree between the target information D and the reference data using, for example, a reference database as a classifier algorithm or an optimized function.

  For example, when the reference database shown in FIG. 4 is used, when the presentation data P included in the target information D matches or is similar to “content A”, “80%”, “ First association degrees of “10%” for “Sustain A” and “1%” for “Presentation B” are calculated. Further, when the voice data S is similar to “speech A” and “speech B”, for example, the association degree between “speech A” and “speech B” and the reference information is multiplied by an arbitrary coefficient. A value is calculated as the first association degree. Further, when the target information D includes a plurality of data, for example, a first association degree corresponding to each of the plurality of data is calculated.

  After calculating the first association degree, the evaluation unit 12 acquires evaluation information including the target information D, the reference information, and the first association degree. Note that the evaluation unit 12 may calculate the first association degree with reference to, for example, the reference database illustrated in FIG. 5 or FIG.

<Update unit 13>
For example, when the relationship between the past target information and the reference information is newly acquired, the update unit 13 reflects the relationship in the association degree. As data to be reflected in the association degree, for example, update data including target information D newly acquired by an administrator or the like and reference information corresponding to the evaluation result R of the target information D is used. In addition, as data to be reflected in the association degree, for example, learning data or the like created based on the evaluation result R by an administrator or the like is used.

<Output unit 14>
The output unit 14 generates an evaluation result R based on the evaluation information, and outputs the evaluation result R. The output unit 14 generates an evaluation result R for the target information D based on, for example, the first association degree of the evaluation information.

  The evaluation result R includes a first evaluation selected from, for example, preset two or more evaluation criteria. As the evaluation criteria, the same items as the reference information described above (planning, sustainability, future potential, presentation ability, estimated health value, estimated age, etc.) are used, and for example, a judgment criterion combining the above items is used. In addition to being set in three or more stages such as 0 to 100 points, the evaluation criteria may be set in two stages, for example, “pass” and “fail”. Evaluation criteria are set in advance by an administrator or the like and stored in the information DB 16.

  The first evaluation is selected from the evaluation criteria based on the reference information included in the evaluation information and the first association degree. The first evaluation is obtained as a result of comprehensive evaluation of the evaluation information, for example, indicating “XX points” selected from the evaluation criteria set to 0 to 100 points. In addition, the first evaluation may be acquired for each evaluation criterion corresponding to each reference information, for example. In this case, the output unit 14 converts, for example, the first association degree included in the evaluation information as the first evaluation, and generates the evaluation result R.

  The output unit 14 outputs the generated evaluation result R. The output unit 14 outputs the evaluation result R to the output part 109 via the I / F 107. For example, the output unit 14 transmits the evaluation result R to the user terminal 2 owned by the proposer via the I / F 105. The output unit 14 transmits, for example, the video of the presentation of the proposer and the evaluation result R to another user terminal owned by another user.

<Input unit 15>
The input unit 15 receives the target information D transmitted from the user terminal 2 via the I / F 105, and receives various types of information input from the input part 108 via the I / F 106, for example. In addition, the input unit 15 may receive, for example, target information D stored in the server 3. The input unit 15 may receive the target information D and the like via a storage medium such as a portable memory. The input unit 15 receives, for example, update data created by an administrator or the like based on the evaluation result R, learning data used to update the association degree, and the like.

<User terminal 2>
The user terminal 2 is held by a proposer who uses the evaluation support system 100. In addition to a personal computer (PC), for example, an electronic device such as a smartphone or a tablet terminal is used as the user terminal 2. The user terminal 2 includes a camera and a microphone for acquiring a video of the proposer's presentation, and a generation unit that generates the target information D based on the acquired video. In addition, the user terminal 2 may have a structure and function equivalent to the evaluation support apparatus 1 mentioned above, for example. That is, for example, the evaluation support system 100 according to the present embodiment may use the user terminal 2 instead of the evaluation support apparatus 1. The user terminal 2 indicates a terminal (another user terminal) owned by another user who performs a public call for presentations, for example.

<Server 3>
The server 3 stores data (database) related to various types of information. In this database, for example, information sent via the public communication network 4 is accumulated. The server 3 may store information similar to the information DB 16, for example, and may transmit and receive various types of information to and from the evaluation support apparatus 1 via the public communication network 4. As the server 3, for example, a database server on a network may be used. The server 3 may be used instead of the storage unit 104 and the information DB 16 described above.

<Public communication network 4>
The public communication network 4 (network) is an Internet network or the like to which the evaluation support apparatus 1 or the like is connected via a communication circuit. The public communication network 4 may be a so-called optical fiber communication network. The public communication network 4 is not limited to a wired communication network, and may be realized by a wireless communication network.

(Embodiment: Operation of Evaluation Support System 100)
Next, an example of the operation of the evaluation support system 100 in the present embodiment will be described. FIG. 9 is a flowchart showing an example of the operation of the evaluation support system 100 in the present embodiment.

<Acquisition means S110>
First, target information D to be evaluated is acquired (acquiring unit S110). The acquisition unit 11 may acquire the target information D via a storage medium such as a portable memory, for example, in addition to acquiring the target information D generated by the user terminal 2 via the input unit 15. The acquisition unit 11 may acquire, for example, person information in addition to the target information D. The acquisition unit 11 may store the acquired target information D and the like in the information DB 16.

  For example, the acquisition unit 11 extracts specific data included in the target information D. In this case, the acquisition unit 11 may store the extracted data in the information DB 16.

  For example, the acquisition unit 11 may acquire each target information D stored for a certain period in addition to continuously acquiring the target information D generated by the user terminal 2. That is, the acquisition unit 11 may acquire the target information D in a lump after the suggestion of the presenter ends, in addition to dividing and acquiring the target information D in a state close to real time during the suggestion of the presenter. The timing at which the acquisition unit 11 acquires the target information D from the user terminal 2 and the number of divisions are arbitrary.

<Evaluation means S120>
Next, with reference to the reference database, evaluation information including the first association degree between the target information D and the reference information is acquired (evaluation means S120). The evaluation unit 12 acquires the target information D from the acquisition unit 11 or the information DB 16 and acquires a reference database from the information DB 16.

  The evaluation unit 12 can calculate the first association degree between the target information D and the reference information by referring to the reference database. For example, the evaluation unit 12 selects past target information that matches, partially matches, or is similar to the target information D, selects reference information associated with the selected past target information, and selects the selected past information. The first association degree is calculated based on the association degree between the target information and the reference information. Note that the evaluation unit 12 may store the calculated first association degree and the acquired evaluation information in the information DB 16.

  For example, the evaluation unit 12 may refer to the reference database illustrated in FIG. 5 to calculate the first association degree between each combination of data included in the target information D and the reference information. Further, the evaluation unit 12 may calculate the first association degree via the intermediate information with reference to, for example, the reference database illustrated in FIG.

<Output means S130>
Next, an evaluation result R is generated based on the evaluation information, and the evaluation result R is output (output unit S130). The output unit 14 transmits the evaluation result R to the user terminal 2 owned by the proposer. The output unit 14 may acquire evaluation data from the evaluation unit 12 or the information DB 16, and may acquire a format for displaying the evaluation result R from the information DB 16, for example.

  The output unit 14 generates an evaluation result R with reference to, for example, a format based on the evaluation information. The evaluation result R may include a first evaluation selected from, for example, preset two or more evaluation criteria.

  For example, as illustrated in FIG. 2B, the output unit 14 calculates scores (scores) for evaluation items such as “planning” and “sustainability” based on the evaluation information. The first evaluation is selected from the output unit 14, for example, a preset evaluation criterion such as 2 to 100 stages. For example, as evaluation criteria corresponding to the first degree of association expressed as a percentage, “Very good: 80 to 100%”, “Good: 60 to 79%”, “Normal: 40 to 59%”, “Bad: 20 to 39” % ”And“ Very bad: 0 to 19% ”are preset, and the output unit 14 first evaluates“ normal ”when the first association degree“ 45% ”is acquired. Choose as.

  The output unit 14 acquires an evaluation criterion from, for example, the information DB 16, and generates and outputs an evaluation result R based on the evaluation information. The output unit 14 may calculate, for example, a value for each first association degree associated with the reference information as a score, or may calculate a value combining the first association degree, an average value, or the like. For example, the output unit 14 may select the first evaluation based on a result of comparing a preset threshold value with the first association degree. In this case, for example, when “80%” is set as the threshold for the evaluation criterion, one of the two levels of the case where the first association degree is 80% or more and less than 80% is the first evaluation. Selected as. For example, the output unit 14 may generate and output the evaluation result R based only on the first evaluation of 80% or more. The threshold condition can be set arbitrarily.

  The output unit 14 may select, for example, text data based on the evaluation information, and generate and output it as a comment of the evaluation result R. In this case, the text data may be stored in the storage unit 104 in a state in which the text data is associated with the reference information or the association degree in advance. That is, the text data may be selected based on at least one of the reference data included in the evaluation information and the first association degree.

  Thereafter, the output unit 14 outputs the evaluation result R. The output unit 14 outputs the evaluation result R to the user terminal 2 or the output part 109. For example, in addition to the evaluation result R, the output unit 14 transmits the video of the presentation of the proposer to another user terminal.

<Update means S140>
Thereafter, for example, when a relationship between past target information and reference information is newly acquired, the relationship may be reflected in the association degree (update unit S140). For example, the update unit 13 acquires update data newly acquired by an administrator or the like, and reflects the update data in the association degree. In addition, the update unit 13 acquires, for example, learning data created by the administrator based on the evaluation result R and reflects it in the association degree.
The update unit 13 calculates and updates the degree of association using, for example, machine learning, and deep learning is used for machine learning, for example.

  Thereby, the operation of the evaluation support system 100 in the present embodiment is completed. Note that whether or not the above-described updating unit S140 is performed is arbitrary.

  According to the present embodiment, the evaluation unit S120 refers to the reference database and acquires evaluation information including the first association degree between the target information D and the reference information. The target information D is generated based on the video of the proposer's presentation. For this reason, the quantitative evaluation result R can be acquired with respect to the content of the presentation of the proposer. Thereby, it is possible to connect the quantitative evaluation result R to the social credibility of the proposer.

  According to the present embodiment, the evaluation result R includes a first evaluation selected from two or more preset evaluations. For this reason, the evaluation result R based on a common evaluation criterion can be output even for presentations in different fields. Thereby, it is possible to obtain a quantitative evaluation result R for presentations in various fields.

  Further, according to the present embodiment, the output unit S130 includes transmitting the video of the proposer's presentation and the evaluation result R to another user terminal. For this reason, for example, when another user who owns another user terminal conducts a public call for presentations, it is possible to support quantitative selection via the evaluation support system 100. As a result, it is possible to reduce the variation in examination criteria caused by the selection person, and it is possible to reduce labor costs and selection time spent for selection.

  In addition, according to the present embodiment, the acquisition unit S110 acquires the target information D generated based on the video of the proposer's presentation in 5 seconds or more and 1 minute or less. For this reason, it is possible to easily obtain the quantitative evaluation result R while suppressing an increase in data.

  Further, according to the present embodiment, when the relationship between the past target information and the reference information is newly acquired, the updating unit S140 reflects the relationship in the association degree. For this reason, the association degree can be easily updated, and the accuracy of the evaluation result R can be further increased.

(First Modification of Operation of Evaluation Support System 100)
Next, a first modified example of the operation of the evaluation support system 100 in the present embodiment will be described with reference to FIG. The difference between the above-described operation and the operation of the first modified example is that the questioning unit S110a and the adding unit S110b are performed. Since the other points are the same as the above-described operation, description thereof will be omitted as appropriate. Note that the inquiry unit S110a and the addition unit S110b may be implemented after the acquisition unit S110, for example, in the acquisition unit S110.

<Question means: S110a>
The question means S110a generates question information Q for the proposer based on the acquired target information D, and outputs the question information Q. The question unit 11a refers to, for example, the question database shown in FIG. 8, obtains three or more levels of first question association between the target information D and past question information, and obtains past question information and first question Question information Q is generated based on the association degree. The question unit 11a may generate and output question information Q corresponding to a plurality of questions, for example. For example, the question unit 11a stores the generated question information Q in the information DB 16.

<Additional means: S110b>
Next, the adding unit S110b acquires answer information A based on the answer of the proposer with respect to the question information Q. The adding unit 11b may add the answer information A to the target information D when acquiring the answer information A as information different from the target information D. In this case, the evaluation unit S120 is performed using the target information D to which the answer information A is added. The adding unit 11b may extract the answer information A from the target information D, for example. In this case, in the adding unit S110b, the acquisition unit 11 acquires the target information D including the answer information A.

  Thereafter, the above-described evaluation unit S120 and the like are performed, and the operation of the evaluation support system 100 in the present embodiment ends.

  According to the first modified example of the operation in the present embodiment, the evaluation unit S120 refers to the reference database, and includes the first association degree between the target information D and the reference information, as in the above-described operation. Get information. The target information D is generated based on the video of the proposer's presentation. For this reason, the quantitative evaluation result R can be acquired with respect to the content of the presentation of the proposer. Thereby, it is possible to connect the quantitative evaluation result R to the social credibility of the proposer.

  In particular, according to the first modified example of the operation in the present embodiment, the question unit S110a generates the question information Q for the proposer and outputs the question information Q. Further, the adding unit S110b obtains answer information A based on the answer of the proposer with respect to the question information Q. For this reason, even when the amount of information included in the presentation of the proposer is small, the answer information A can be acquired using the question information Q, and the amount of information can be supplemented. Thereby, the accuracy of the evaluation result R can be improved.

(Second Modification of Operation of Evaluation Support System 100)
Next, with reference to FIG. 11, the 2nd modification of operation | movement of the evaluation assistance system 100 in this embodiment is demonstrated. The difference between the operation of the first modification described above and the operation of the second modification is that after the evaluation unit S120 is performed, the question unit S110a and the addition unit S110b are performed, and the evaluation unit S120 is performed again. . Since the other points are the same as the above-described operation, description thereof will be omitted as appropriate.

  The question unit S110a refers to the question database shown in FIG. 12, for example, and generates the question information Q. The question database shown in FIG. 12 is different from the question database shown in FIG. 8 in that the reference information held in the reference database is linked to the past question information by the question relevance. That is, based on the evaluation information acquired in the evaluation unit S120, the question unit S110a and the addition unit S110b are implemented.

  In the operation of the second modification, in the adding unit S110b, the acquisition unit 11 acquires the target information D including the answer information A. Thereafter, the evaluation unit S120 is performed again based on the target information D including the answer information A.

  Thereafter, the above-described output means S130 and the like are implemented, and the operation of the evaluation support system 100 in the present embodiment ends.

  According to the second modified example of the operation in the present embodiment, the evaluation unit S120 refers to the reference database, and includes the first association degree between the target information D and the reference information, as in the above-described operation. Get information. The target information D is generated based on the video of the proposer's presentation. For this reason, the quantitative evaluation result R can be acquired with respect to the content of the presentation of the proposer. Thereby, it is possible to connect the quantitative evaluation result R to the social credibility of the proposer.

  In particular, according to the second modification of the operation in the present embodiment, the question unit S110a generates the question information Q with reference to the evaluation information. For this reason, the question information Q according to the evaluation information can be generated. Thereby, it becomes possible to further improve the accuracy of the evaluation result R.

  According to the above-described embodiment, the target information D can be evaluated based on the association degrees set in three or more stages (first association degree, question association degree, first question association degree, similarity degree). There are features. The association degree can be described by a numerical value of 0 to 100%, for example, and may be configured at any stage as long as it can be described by three or more numerical values.

  In the reference information selected as a candidate of the evaluation result R for the target information D based on such association degree, reference information and the like (past question information, intermediate information) may be displayed in descending order of association degree. It becomes possible. Thus, by displaying in the order of the association degrees and the like, the manager or the like can preferentially select a tendency that is highly likely to correspond to the proposer. On the other hand, since a tendency that is unlikely to be a proposal can be displayed without being excluded, the administrator or the like can make a selection without missing it.

  In addition to the above, according to the above-described embodiment, even when the relevance or the like is extremely low such as 1%, it is possible to evaluate without overlooking. Even reference information or the like having an extremely low association degree indicates that it is connected as a slight sign, and it is possible to suppress oversight and misperception.

  Moreover, according to embodiment mentioned above, in the acquisition means S110, the acquisition part 11 may acquire the attention degree of the proposer in a social networking service, for example. For example, the number of followers such as Twitter (registered trademark) and Facebook (registered trademark) is used as the degree of attention of the proposer, and the degree of connection with other users is used. For this reason, information other than the content of the presentation of the proposer can be targeted for the evaluation result R. As a result, it is possible to easily generate an optimal evaluation result R according to the field and situation of the presentation.

  Further, according to the above-described embodiment, the presenter's presentation may include a corporate advertisement. For this reason, the presentation content can be evaluated in a non-known state.

  Further, according to the embodiment described above, the target information D may be information excluding a person's video. For this reason, it is possible to quantitatively evaluate a company's products and creations.

  Further, according to the above-described embodiment, the target information D includes the action of the proposer. For this reason, it is possible to quantitatively evaluate the skill and the like of the proposer.

  Further, according to the above-described embodiment, the video of the proposer is desirably 5 seconds or more and 1 minute or less, and more preferably 5 seconds or more and 30 seconds or less. Thereby, it is possible to easily realize the quantitative evaluation result R while suppressing an increase in data.

  Further, according to the above-described embodiment, the language used by the proposer for the presentation is arbitrary, and the quantitative evaluation result R can be realized in any language. That is, the target information D may be generated based on a presentation using a native language or multilingual by the proposer.

  Further, according to the above-described embodiment, the target information D may be generated based on a presentation video of one or a plurality of proposers, a company introduction, or the like. That is, the proposer does not have to be taken in the presentation video.

  In addition, according to the above-described embodiment, for example, the proposer may be able to continue the presentation multiple times (for example, every day, every week, etc.). In this case, in addition to generating different target information D for each presentation, target information D in which a plurality of presentations are collected may be generated.

  Further, according to the above-described embodiment, the target information D may be generated, for example, based on a presentation video for the purpose of funding or supporting a world adventure that the proposer takes several months to several years.

  In addition, according to the above-described embodiment, the target information D may be generated based on a video of a presentation for the purpose of procuring funds necessary for an athlete, for example, if the proposer is an athlete or an athlete supporter. Good.

  Further, according to the above-described embodiment, the target information D may be generated based on, for example, a presentation video for the purpose of requesting or providing support other than funds by the proposer. In addition, at least one of credit, electronic money, points, and virtual currency is used, for example, human support, educational support, technical guidance, and the like may be used.

  In addition, according to the above-described embodiment, the target information D may be generated based on a video of a presentation for the purpose of searching for a side job, a job search, or a human support at a time when the proposer is vacant, for example. Good. For example, as a video of a presentation, “Help me move”, “I will accompany you to shopping”, “I will guide you around the city”, “I will take on a fashion consultation”, “I will be in touch with you”, “I will talk about anything casually” An image based on a description of specific implementation content such as “” may be used. In addition, as a presentation video, a video based on an explanation of contents to be delivered such as buckwheat or pizza may be used.

  Further, according to the above-described embodiment, the target information D may be generated, for example, based on a video of a presentation for the purpose of providing or providing a human request such as care or nursing by the proposer.

  Further, according to the above-described embodiment, the proposal information D may be generated based on, for example, a presentation video for the purpose of buying and selling merchandise.

  Further, according to the above-described embodiment, the proposal information D may be generated based on a video of a presentation for the purpose of obtaining an estimate of a place where the proposer wants to go and where to stay.

  Further, according to the above-described embodiment, the target information D may be generated based on a presentation video for the purpose of exchanging time with the proposer and buying and selling time.

  Further, according to the above-described embodiment, the target information D may be generated based on a presentation video for the purpose of providing or providing a human request such as a periodic request such as a babysitter by the proposer.

  Further, according to the above-described embodiment, the target information D may be generated based on a presentation video for the purpose of supporting a person, service, system, or the like that the proposer wants to support.

  In addition, according to the above-described embodiment, the target information D may be generated based on a video in which a performance such as a suggestor's performance or performance is used as a presentation. In this case, the proposer generates the target information D for the purpose of attracting customers or funding, for example.

  Moreover, according to embodiment mentioned above, based on the numerical value of the evaluation result R acquired for every proposer, you may enable it to trade a numerical value freely between proposers like a virtual currency. For example, a proposer having a high evaluation result R may be able to transfer, lend, deposit, etc. the evaluation result R with respect to a proposer with a low evaluation result R. In addition, based on the value of the evaluation result R of the proposer, purchase evaluation of other proposers is purchased, and even if the value of the evaluation result R on hand temporarily becomes negative, replenishment, appropriation, and settlement within a certain period Etc. may be made possible.

  In the above, for example, when there is a proposer whose numerical value of the evaluation result R is extremely high, there is a possibility that numerical fluidity cannot be expected. For this reason, the proposer may be able to transfer the numerical value to another proposer or user. In this case, for example, the proposer can be transferred to a proposer in a field having a market value equivalent to the field of the numerical value owned.

  Further, according to the above-described embodiment, at least one of the presentation video, the target information D, and the evaluation result R may be transmitted to a terminal (another user terminal) owned by another user. At this time, two-way communication between the user terminal 2 of the proposer and another user terminal may be realized. In addition, the number of the proposer's user terminals 2 and other user terminals is arbitrary.

  Further, according to the above-described embodiment, for example, the portion that is the point of the evaluation result R can be confirmed with respect to the target information D, and can be confirmed, for example, in a text format. For this reason, the proposer can easily improve the presentation.

  Moreover, according to embodiment mentioned above, another user can comment on the target information D. In addition, the proposer can respond to comments of other users. For this reason, it is possible to make use of the realistic sensation unique to the video of the presentation. Further, for example, the name of another user who supports the proposer can be included in the video of the presentation by the proposer, and the closeness between the proposer and the other user can be improved.

  In addition, according to the above-described embodiments, as presentation images, in addition to products such as clothes, decorations, furniture, food, homes, land, real estate, etc., for example, personal information on the Internet (for example, Facebook (registered trademark), etc.) An image based on the content related to buying and selling and rental to (used account) may be used. For example, when a presentation video about clothes is used, other users can also check information that is not known unless the product is actually available, such as the texture of the fabric, comfort and size. It is also possible to support the buying and selling and renting of goods through the evaluation support system 100.

  In addition, according to the above-described embodiment, it is possible to notify other users of the schedule and content notification when the proposer captures the video of the presentation. Therefore, other users can check the presentation video of the interested proposer based on the presentation video and the evaluation result R without missing the presentation video. In addition, when the user is interested in the proposer, the acquisition of the target information D can be requested in advance.

  Further, according to the above-described embodiment, for example, the target information D of only the proposer who has won a pre-executed game or quiz may be acquired and transmitted to another user. In this case, since only the target information D of the proposer selected in advance is provided to other users, the quality of the target information D can be improved.

  In addition, according to the above-described embodiment, a video of a presentation between a plurality of proposers who are familiar with a specific specialized field may be used, and a plurality of specified proposers such as a team, a group, an organization, a corporation, etc. Equivalent presentation video may be used. For this reason, the quantitative evaluation result R can be acquired for the target information D in various fields.

  Further, according to the above-described embodiment, contents related to business investment may be used as a presentation video. For this reason, other users can consider the determination of business investment via the evaluation support system 100.

  Further, according to the above-described embodiment, a video based on a description of the contents related to outsourcing or outsourcing of manufacturing may be used as the video of the presentation. For this reason, it is possible to acquire a quantitative evaluation result R based on presentation videos at a plurality of companies, and it is possible to easily select a contractor company or the like.

  Further, according to the above-described embodiment, another user may select a field of interest and acquire a video or the like of the proposal of the proposer in the selected field. Further, an additional service may be provided after obtaining the video of the presentation of the proposer. For example, when a social problem that other users are interested in is selected, the social problem includes support and support for sick children. Based on the social issues, groupings of presentation videos and the like are performed, and other users can donate to groups that are interested.

  Further, according to the above-described embodiment, as a presentation video, for example, a video based on the content of recommending another proposer may be used. For this reason, in addition to the evaluation result R that quantitatively evaluates the content of the presentation, it is possible to confirm the degree to which the proposer is supported by other proposers.

  Although the embodiments of the present invention have been described, the embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the scope of the invention. These embodiments and modifications thereof are included in the scope and gist of the invention, and are included in the invention described in the claims and the equivalents thereof.

1: Evaluation support device 2: User terminal 3: Server 4: Public communication network 10: Case 11: Acquisition unit 11a: Questioning unit 11b: Addition unit 12: Evaluation unit 13: Update unit 14: Output unit 15: Input unit 16 : Information DB
100: Evaluation support system 101: CPU
102: ROM
103: RAM
104: Storage unit 105: I / F
106: I / F
107: I / F
108: input portion 109: output portion 110: internal bus S110: acquisition means S110a: inquiry means S110b: addition means S120: evaluation means S130: output means S140: update means

Claims (9)

An evaluation support system that evaluates the content of a proposal of a proposer via a user-limited network,
Acquisition means for acquiring target information generated based on the video of the presenter's presentation;
Reference database in which past target information acquired in advance, reference information used for evaluation of the past target information, and three or more levels of association between the past target information and the reference information are stored When,
An evaluation unit that refers to the reference database and obtains evaluation information including first relations of three or more stages between the target information and the reference information;
An output means for generating an evaluation result based on the evaluation information and transmitting the evaluation result to a terminal held by the proposer;
An evaluation support system characterized by comprising: The evaluation support system according to claim 1, wherein the evaluation result includes a first evaluation selected from two or more preset evaluation criteria. The evaluation support system according to claim 1, wherein the output unit includes transmitting the video of the presentation of the proposer and the evaluation result to another user terminal. The evaluation support system according to any one of claims 1 to 3, wherein the presentation of the proposer includes a corporate advertisement. The evaluation support system according to claim 1, wherein the target information is information excluding a person's video. The evaluation support system according to claim 1, wherein the target information includes an action of the proposer. The evaluation support according to any one of claims 1 to 6, wherein the acquisition unit acquires the target information generated based on a video of the presentation of the proposer for 5 seconds to 1 minute. system. 8. The update apparatus according to claim 1, further comprising an update unit configured to reflect the relationship in the association degree when a relationship between the past target information and the reference information is newly acquired. The evaluation support system according to claim 1.
An evaluation support apparatus for evaluating the content of a presentation of a proposer registered in a user-limited network,
An acquisition unit for acquiring target information generated based on the video of the presentation of the proposer;
Reference database in which past target information acquired in advance, reference information used for evaluation of the past target information, and three or more levels of association between the past target information and the reference information are stored When,
An evaluation unit that refers to the reference database and obtains evaluation information including first relations of three or more stages between the target information and the reference information;
An output unit that generates an evaluation result based on the evaluation information and transmits the evaluation result to a terminal held by the proposer;
An evaluation support apparatus comprising:

Images