Text sending method, device, electronic device and computer readable medium

Abstract

The embodiments of the present disclosure disclose a text sending method, device, electronic device and computer-readable medium. A specific implementation of the method includes: obtaining a database of projects to be evaluated and target users; determining the project scale level; screening the target user information set to obtain the screened target user information set as a candidate user information set; obtaining the first-level user academic feature information set and user introduction information corresponding to each candidate user information; generating a second-level user academic feature information set corresponding to each candidate user information; fusing the first-level user academic feature information set group with the second-level user academic feature information set group; determining the candidate user information corresponding to the evaluation task as the evaluation user information; for each evaluation user information, sending the corresponding customized project invitation text to the terminal device corresponding to the evaluation user information. This implementation can accurately determine the optimal evaluation user who can participate in the project to be evaluated.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and in particular to a text sending method, device, electronic device, and computer-readable medium. Background Art

[0002] Project Evaluation can be a comprehensive evaluation of the planning, design and implementation of the proposed project from an overall perspective based on the feasibility study of the project. The selection of project evaluators is usually done by manually drawing lots to extract information on multiple project evaluators from the personnel information database.

[0003] However, the inventors have found that when the above method is used to select project evaluators, the following technical problems often occur:

[0004] First, the personnel selection method was too random. The evaluators were not selected based on the overall situation of the project and the personnel situation in the personnel information database, resulting in inaccurate evaluation of the project using multiple project evaluators selected.

[0005] Second, there may be situations where project evaluators pretend to participate in the project to be evaluated, resulting in poor project evaluation results.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the inventive concept and therefore it may contain information that does not form the prior art that is already known in this country to a person of ordinary skill in the art. Summary of the invention

[0007] The content of this disclosure is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this disclosure is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0008] Some embodiments of the present disclosure propose a text sending method, apparatus, electronic device, and computer-readable medium to solve one or more of the technical problems mentioned in the above background technology section.

[0009] In a first aspect, some embodiments of the present disclosure provide a text sending method, comprising: obtaining a project to be evaluated and a target user database, wherein the target user database stores user data of each target user information in a target user information set; determining the project scale level of the project to be evaluated based on the project category, project number and project estimated value information of the project to be evaluated; screening the target user information set according to the project scale level to obtain a screened target user information set as a candidate user information set; obtaining a first-level user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set from the target user database to obtain a first-level user academic feature information set group and a user introduction information set; generating the candidate information set according to the user introduction information set. A secondary user academic feature information set corresponding to each candidate user information in the user information set is obtained to obtain a secondary user academic feature information set group; the feature information of the above-mentioned primary user academic feature information set group and the above-mentioned secondary user academic feature information set group are fused to obtain a fused user academic feature information set group; based on the above-mentioned fused user academic feature information set group, the candidate user information in the above-mentioned candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated is determined as the evaluation user information to obtain at least one evaluation user information; for each evaluation user information in the above-mentioned at least one evaluation user information, the customized project invitation text corresponding to the above-mentioned evaluation user information is sent to the terminal device corresponding to the above-mentioned evaluation user information, so that the evaluation user corresponding to the above-mentioned evaluation user information can confirm on the terminal device whether to participate in the above-mentioned evaluation task.

[0010] In a second aspect, some embodiments of the present disclosure provide a text sending device, comprising: a first acquisition unit, configured to acquire a project to be evaluated and a target user database, wherein the target user database stores user data of each target user information in a target user information set; a first determination unit, configured to determine the project scale level of the project to be evaluated based on the project category, project number and project estimated value information of the project to be evaluated; a screening unit, configured to screen the target user information set according to the project scale level, and obtain a screened target user information set as a candidate user information set; a second acquisition unit, configured to acquire a first-level user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set from the target user database, and obtain a first-level user academic feature information set group and a user introduction information set; a generation unit, configured to generate a first-level user academic feature information set group and a user introduction information set according to the user introduction information set; A first information set is configured to generate a second-level user academic feature information set corresponding to each candidate user information in the candidate user information set to obtain a second-level user academic feature information set group; a fusion unit is configured to fuse feature information of the first-level user academic feature information set group with the second-level user academic feature information set group to obtain a fused user academic feature information set group; a second determination unit is configured to determine, according to the fused user academic feature information set group, the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as the evaluation user information to obtain at least one evaluation user information; a sending unit is configured to send the customized project invitation text corresponding to the above-mentioned evaluation user information to the terminal device corresponding to the above-mentioned evaluation user information for each evaluation user information in the above-mentioned at least one evaluation user information, so that the evaluation user corresponding to the above-mentioned evaluation user information can confirm whether to participate in the above-mentioned evaluation task on the terminal device.

[0011] In a third aspect, some embodiments of the present disclosure provide an electronic device comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner in the first aspect.

[0012] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium having a computer program stored thereon, wherein when the program is executed by a processor, the method described in any implementation manner in the first aspect is implemented.

[0013] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the text sending method of some embodiments of the present disclosure can accurately determine the optimal evaluation user who can participate in the project to be evaluated. Specifically, the reason for the inaccurate determination of the relevant evaluation users is that the personnel selection method is too random, and the evaluation personnel are not selected according to the overall situation of the project and the personnel situation in the personnel information database, resulting in the problem of inaccuracy in the evaluation of the project using the selected multiple project evaluation personnel. Based on this, the text sending method of some embodiments of the present disclosure first obtains the project to be evaluated and the target user database for subsequent selection of evaluation users. Among them, the above-mentioned target user database stores the user information of each target user information in the target user information set. Then, according to the project category, project number and project estimated value information of the above-mentioned project to be evaluated, the project scale level of the above-mentioned project to be evaluated can be accurately determined. Here, the obtained project scale level is used for the preliminary screening of the target user information to narrow the selection range of the evaluation personnel. Then, according to the above-mentioned project scale level, the above-mentioned target user information set is preliminarily screened to obtain the screened target user information set as the candidate user information set. In order to narrow the selection range, a more accurate evaluation personnel can be selected later. Next, the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set are obtained from the target user database to obtain the first-level user academic feature information set group and the user introduction information set. Here, by obtaining the first-level user academic feature information set and the user introduction information corresponding to each user information, it is convenient to further narrow the user selection range through some characteristic information of the user in the subsequent process. Further, according to the user introduction information set, the second-level user academic feature information set corresponding to each candidate user information in the candidate user information set is generated to obtain the second-level user academic feature information set group. Here, through the user introduction information, some second-level user academic feature information for the corresponding candidate user information can be determined, so as to facilitate the subsequent comprehensive screening of the evaluators who can finally participate in the evaluation project according to the user academic feature information. Next, the first-level user academic feature information set group and the second-level user academic feature information set group are subjected to feature information fusion to obtain the fused user academic feature information set group. Furthermore, according to the fused user academic feature information set group, the candidate user information in the candidate user information set that can participate in the corresponding evaluation task of the above-mentioned project to be evaluated can be accurately determined as the evaluation user information, and at least one evaluation user information is obtained. Finally, for each evaluation user information in the at least one evaluation user information, the customized project invitation text corresponding to the evaluation user information is sent to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information can confirm whether to participate in the evaluation task on the terminal device.Therefore, the present disclosure selects evaluators according to the overall situation of the project and the personnel situation in the personnel information database, and can accurately determine at least one evaluator user who can participate in the above-mentioned evaluation task. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0015] Figure 1 is a flowchart of some embodiments of the text sending method according to the present disclosure;

[0016] Figure 2 is a schematic structural diagram of some embodiments of a text sending device according to the present disclosure;

[0017] Figure 3 It is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION

[0018] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0019] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0020] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0021] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0022] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0023] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0024] refer to Figure 1 , shows a process 100 of some embodiments of the text sending method according to the present disclosure. The text sending method comprises the following steps:

[0025] Step 101: Obtain the project to be evaluated and the target user database.

[0026] In some embodiments, the execution subject of the above-mentioned text sending method can obtain the project to be evaluated and the target user database through a wired connection method or a wireless connection method. Among them, the above-mentioned target user database stores the user information of each target user information in the target user information set. The target user database can be a target user information database. The target user information can be the user information of the target user. The target user can be an expert in the evaluable project. The above-mentioned expert can evaluate the feasibility of the project, the completeness of the project plan, the implementation of the project, etc. In practice, the user information can include but is not limited to at least one of the following: user name, user age, user title, user work information, user honor information.

[0027] Step 102: Determine the project scale level of the project to be evaluated based on the project category, project staff and project estimated value information of the project to be evaluated.

[0028] In some embodiments, the above-mentioned execution entity can determine the project scale level of the above-mentioned project to be evaluated based on the project category, project number and project estimated value information of the above-mentioned project to be evaluated. Among them, the project category of the project to be evaluated can be the industry category involved in the project to be evaluated. For example, the project category can be a food project category, or it can be a water conservancy construction project category. The number of project people can be the number of project workers in the project to be evaluated. The project estimated value information can be the investment amount information of the project to be evaluated. The project scale level can characterize the scale of the project. For example, the project scale level can be divided into: level 1 project level, level 2 project level, and level 3 project level. The project scale of the project corresponding to the level 1 project level is greater than the project scale of the project corresponding to the level 2 project level. The project scale of the project corresponding to the level 2 project level is greater than the project scale of the project corresponding to the level 3 project level.

[0029] As an example, the execution entity may input the project category, project headcount and project estimated value information of the project to be evaluated into a project scale level determination model to generate a project scale level for the project to be evaluated. The project scale level determination model may be a classification task model. For example, the project scale level determination model may be a logistic regression model.

[0030] Step 103 , screening the target user information set according to the project scale level to obtain a screened target user information set as a candidate user information set.

[0031] In some embodiments, the execution entity may filter the target user information set in various ways according to the project scale level to obtain a filtered target user information set as a candidate user information set.

[0032] In some optional implementations of some embodiments, the above-mentioned information screening of the target user information set according to the above-mentioned project scale level to obtain a screened target user information set as a candidate user information set may include the following steps:

[0033] The first step is to determine the user screening area information for the above-mentioned project to be evaluated based on the above-mentioned project scale level.

[0034] As an example, in response to determining that the project scale level is a level 1 project level, the regional information corresponding to the province where the development address of the above-mentioned project to be evaluated is located is determined as the user screening regional information of the project to be evaluated. In response to determining that the project scale level is a level 2 project level, the regional information corresponding to the city where the development address of the above-mentioned project to be evaluated is located is determined as the user screening regional information of the project to be evaluated. In response to determining that the project scale level is a level 3 project level, the regional information corresponding to the district where the development address of the above-mentioned project to be evaluated is located is determined as the user screening regional information of the project to be evaluated.

[0035] The second step is to obtain the address information of each target user information in the target user information set from the target user database.

[0036] The third step is to remove the target user information whose address information corresponding to the address is not located in the area corresponding to the user screening area information from the target user information set to obtain a first removed target user information set.

[0037] The fourth step is to obtain the nucleic acid test information of each target user information in the target user information set after the first removal from the target user database, wherein the nucleic acid test information may be the nucleic acid test result of the user within 72 hours.

[0038] The fifth step is to remove the target user information whose corresponding nucleic acid test information is no nucleic acid test or the nucleic acid test result is positive from the above-mentioned first removed target user information set, and obtain the second removed target user information set as the above-mentioned candidate user information set.

[0039] Step 104, obtaining the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the above-mentioned candidate user information set from the above-mentioned target user database, and obtaining a first-level user academic feature information set group and a user introduction information set.

[0040] In some embodiments, the above-mentioned execution subject can obtain the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the above-mentioned candidate user information set from the above-mentioned target user database, and obtain the first-level user academic feature information set group and the user introduction information set. The academic features of the first-level user can characterize the user's mastery of the academic branches in the academic field. The academic feature information of the first-level user can be the mastery of the various academic branches in the academic field by the user (i.e., the expert). For example, for the user who is an expert in the computer field, the corresponding first-level user academic feature can be one of the following: algorithm branch, front-end branch, metaverse branch, back-end branch. The corresponding first-level user academic feature information includes: proficient in algorithm research, proficient in front-end language, proficient in metaverse development, and proficient in back-end language. The user introduction information can be the user's profile information. Among them, the user introduction information includes the user's personal honors and deeds information.

[0041] Step 105, based on the above user introduction information set, generate a secondary user academic feature information set corresponding to each candidate user information in the above candidate user information set to obtain a secondary user academic feature information set group.

[0042] In some embodiments, the above-mentioned execution subject can generate a secondary user academic feature information set corresponding to each candidate user information in the above-mentioned candidate user information set in various ways according to the above-mentioned user introduction information set, and obtain a secondary user academic feature information set group. The secondary user academic characteristics can characterize the user's mastery of various types of content under the academic branch. Due to the differences in academic branches, the corresponding types of content can be pre-divided. The secondary user academic feature information is information about the user's (i.e., expert) mastery of various types of content under the academic branch. For example, for an academic branch that is an algorithm branch, the corresponding secondary user academic feature information can be one of the following: data structure algorithm, artificial intelligence algorithm.

[0043] In some optional implementations of some embodiments, generating a secondary user academic feature information set corresponding to each candidate user information in the candidate user information set according to the user introduction information set may include the following steps:

[0044] For each user introduction information in the above user introduction information set, perform the following information generation steps:

[0045] Sub-step 1: segment the user introduction information to obtain a word set.

[0046] As an example, the execution subject may utilize the Jieba word segmentation tool to perform word segmentation processing on the user introduction information to obtain a word set.

[0047] Sub-step 2: removing words whose part of speech category is the target category from the above word set to obtain a first removed word set. The above target category may be a function word category.

[0048] Sub-step 3, obtaining a preset user academic feature information table.

[0049] Among them, the user academic characteristic information table includes: secondary user academic characteristic information corresponding to various types of content under each academic branch. For example, the academic branch is the algorithm branch. The various types of content include: data structure algorithm and artificial intelligence algorithm. The corresponding secondary user academic characteristic information set includes: proficient in data structure algorithm, not proficient in data structure algorithm, proficient in artificial intelligence algorithm and not proficient in artificial intelligence algorithm.

[0050] Sub-step 4, word encoding is performed on each word in the above-mentioned first removed word set to obtain a word vector set.

[0051] As an example, the execution subject may input each word in the first removed word set into a coding model to generate a word vector set, wherein the coding model may be a Transformer coding model.

[0052] Sub-step 5, encoding each user academic feature information included in the above user academic feature information table to obtain a coding vector set.

[0053] As an example, the execution subject may input each user academic feature information included in the user academic feature information table into a coding model to generate a coding vector set, wherein the coding model may be a Transformer coding model.

[0054] Sub-step 6, for each word vector in the word vector set, determining the vector distance between the above word vector and each encoding vector in the above encoding vector set.

[0055] As an example, the execution entity may determine the cosine distance between the word vector and the encoding vector.

[0056] Sub-step 7, removing words whose corresponding vector distances are greater than the target distance from the first removed word set to obtain a second removed word set.

[0057] Sub-step 8, input the above-mentioned second removed word set and the above-mentioned academic feature information of each user into the multi-headed self-attention network model to obtain a first weight set. Among them, the first weight represents the degree of correlation between the user's academic feature information and the words in the second removed word set. The above-mentioned first weight can be a value between 0-1. The larger the value of the first weight, the greater the degree of correlation between the user's academic feature information and the words.

[0058] Sub-step 9, according to the above-mentioned first weight set, remove at least one word from the above-mentioned second removed word set to obtain a third removed word set as the above-mentioned secondary user academic feature information set.

[0059] As an example, the execution entity may remove words whose corresponding first weights are less than a preset value from the second removed word set to obtain a third removed word set as the secondary user academic feature information set.

[0060] Step 106, fusing the feature information of the first-level user academic feature information set group and the second-level user academic feature information set group to obtain a fused user academic feature information set group.

[0061] In some embodiments, the execution entity may fuse the feature information of the primary user academic feature information set group with the secondary user academic feature information set group to obtain a fused user academic feature information set group.

[0062] As an example, for each candidate user information in the candidate user information set, the following information generation steps are performed:

[0063] The first step is to determine the first-level user academic feature information set and the second-level user academic feature information set corresponding to the above-mentioned candidate user information as the first-level target user academic feature information set and the second-level target user academic feature information set.

[0064] In the second step, through the association relationship between academic branches and content types, the academic feature information set of the first-level target users and the academic feature information set of the second-level target users are fused to obtain a fused information set.

[0065] Step 107, based on the above-mentioned fused user academic feature information set group, determine the candidate user information in the above-mentioned candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as the evaluation user information, and obtain at least one evaluation user information.

[0066] In some embodiments, the execution subject may determine the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as evaluation user information in various ways based on the above-mentioned fused user academic feature information set group, and obtain at least one evaluation user information.

[0067] In some optional implementations of some embodiments, determining, according to the above-mentioned fused user academic feature information set group, candidate user information in the above-mentioned candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as evaluation user information, and obtaining at least one evaluation user information may include the following steps:

[0068] The first step is to perform a multi-edge graph generation step for each fused user academic feature information in the above fused user academic feature information set group:

[0069] Sub-step 1: Encode the primary user academic feature information in the first key-value pair included in the above-mentioned fused user academic feature information to obtain an information encoding vector.

[0070] Sub-step 2: multiply the information coding vector by the first numerical value to obtain a first multiplied vector.

[0071] Sub-step 3, determining the word vector corresponding to the secondary user academic feature information in the second key-value pair included in the above-mentioned fused user academic feature information.

[0072] Sub-step 4: multiply the word vector by the second value to obtain a second multiplied vector.

[0073] Sub-step 5: concatenate the first multiplied vector and the second multiplied vector to obtain a concatenated vector.

[0074] Sub-step 6: Input the above concatenated vector into the second multi-head attention mechanism network model to obtain a second weight set, wherein the second weight represents the degree of correlation between the concatenated vector and each preset user's academic ability information.

[0075] Sub-step 7, generating a user capability polygon graph for each preset user academic capability information according to the second weight set.

[0076] In the second step, according to the user capability polygon graph corresponding to each candidate user information in the candidate user information set, determine the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as the evaluation user information, and obtain at least one evaluation user information.

[0077] Step 108, for each evaluation user information in the at least one evaluation user information, the customized project invitation text corresponding to the evaluation user information is sent to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information can confirm whether to participate in the evaluation task on the terminal device.

[0078] In some embodiments, for each evaluation user information in the at least one evaluation user information, the execution entity may send the customized project invitation text corresponding to the evaluation user information to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information may confirm whether to participate in the evaluation task on the terminal device. Each evaluation user information has a unique corresponding customized project invitation text. The text content of the customized project invitation text may include: the task execution time of the evaluation task corresponding to the project to be evaluated, the task execution location, and the evaluation personnel invitation information. For example, the evaluation personnel invitation information may be: "Welcome "Li**" to participate in this project evaluation task."

[0079] In some optional implementations of some embodiments, after step 108, the steps further include:

[0080] The first step is to generate a task participant list text for the evaluation task in response to receiving participation information sent by each evaluation user information in the at least one evaluation user information, wherein the participation information represents the evaluation user's participation in the evaluation task.

[0081] The second step is to send the text of the task participant list to the review end to review the at least one evaluation user information.

[0082] In the third step, in response to the at least one evaluation user information being reviewed and approved, a list of required materials representing participation in the evaluation task is sent to a terminal device corresponding to each evaluation user.

[0083] Optionally, in response to the at least one evaluation user information being reviewed and approved, after sending a list of required materials representing participation in the evaluation task to a terminal device corresponding to each evaluation user, the step further includes:

[0084] The first step is to receive the face photos sent by each evaluation user to obtain a face photo set.

[0085] In the second step, a user attribute is randomly selected from each user attribute as the target user attribute. For example, each user attribute includes: user name, user age, user residence. The above target user attribute can be user name.

[0086] The third step is to determine the attribute information of the target user attributes corresponding to each evaluation user.

[0087] As an example, when the target user attribute is a user name, the execution subject may determine the user name of each evaluation user.

[0088] The fourth step is to generate entry reference coding information for each evaluation user based on the face photo set and the attributes of each target user.

[0089] In the fifth step, in response to detecting the entry information of each evaluation user when the evaluation task is being carried out, the face photo of each evaluation user is collected in real time.

[0090] The sixth step is to generate entry coding information for each evaluation user based on the facial photos of each evaluation user and the corresponding attribute information.

[0091] Step 7: For each evaluation user, perform the following real user determination steps:

[0092] The first sub-step is to determine the coding information similarity between the entry coding information corresponding to the evaluation user and the corresponding entry reference coding information.

[0093] The second sub-step is, in response to determining that the encoding information similarity is less than the target value, determining that the above-mentioned evaluation user is not a real user.

[0094] The third sub-step is, in response to determining that the above-mentioned evaluation user is not a real user, reminding relevant testing personnel to manually test the authenticity of the evaluation user through a paging device.

[0095] A fourth sub-step, in response to determining that the encoding information similarity is greater than or equal to the target value, determines that the above-mentioned evaluation user is a real user.

[0096] Optionally, the above-mentioned generating the admission code information for each evaluation user according to the facial photos of each evaluation user and the corresponding attribute information may include the following steps:

[0097] For each evaluation user, the following encoding information generation steps are performed:

[0098] The first sub-step is to perform vector encoding processing on the attribute information of the above-mentioned evaluation user to obtain an attribute vector.

[0099] As an example, the above execution entity may input the attribute information of the evaluated user into a pre-trained Bert pre-trained model to obtain an attribute vector.

[0100] In the second sub-step, the attribute vector is adjusted to have the same vector dimension as the matrix vector dimension corresponding to the facial photo of the evaluated user, to obtain an adjusted attribute vector.

[0101] In the third sub-step, the adjusted attribute vector is superimposed in depth and orientation with the corresponding matrix of the facial photo of the evaluated user to obtain a superposition matrix.

[0102] The fourth sub-step is to obtain a random number.

[0103] The fifth sub-step is to determine a multi-layer serially connected convolutional neural network for the random number, wherein the number of convolutional neural networks included in the serially connected convolutional neural network is the same as the random number.

[0104] The sixth sub-step is to input the superposition matrix into a multi-layer serially connected convolutional neural network to output the admission coding information for the evaluation user.

[0105] The above-mentioned "optional content" as one of the invention points solves the second technical problem that "there may be a situation where project evaluators pretend to participate in the project to be evaluated, resulting in poor project evaluation results." Based on this, the present disclosure can more accurately determine whether the evaluators participating in the project to be evaluated are the real scheduled personnel by evaluating the corresponding entry code information of the user and the corresponding entry reference code information.

[0106] Optionally, the review end reviews the at least one evaluation user information through the following steps:

[0107] The first step is to obtain the evaluation user information set of each historical evaluation project in the historical evaluation project set to obtain an evaluation user information set group.

[0108] In the second step, for each evaluation user information set in the evaluation user information set group, the number of evaluation user information that is the same between the evaluation user information set and the at least one evaluation user information is determined.

[0109] The third step is to select historical evaluation items whose corresponding number is greater than a predetermined value from the above historical evaluation item set as comparative evaluation items to obtain a comparative evaluation item set.

[0110] In the fourth step, in response to determining that the start time of a corresponding project in the comparison and evaluation project set is greater than a predetermined time period than the start time of the project to be evaluated, determining that the at least one evaluation user information is approved.

[0111] The above-mentioned embodiments of the present disclosure have the following beneficial effects: the text sending method of some embodiments of the present disclosure can accurately determine the optimal evaluation user who can participate in the project to be evaluated. Specifically, the reason for the inaccurate determination of the relevant evaluation users is that the personnel selection method is too random, and the evaluation personnel are not selected according to the overall situation of the project and the personnel situation in the personnel information database, resulting in the problem of inaccuracy in the evaluation of the project using the selected multiple project evaluation personnel. Based on this, the text sending method of some embodiments of the present disclosure first obtains the project to be evaluated and the target user database for subsequent selection of evaluation users. Among them, the above-mentioned target user database stores the user information of each target user information in the target user information set. Then, according to the project category, project number and project estimated value information of the above-mentioned project to be evaluated, the project scale level of the above-mentioned project to be evaluated can be accurately determined. Here, the obtained project scale level is used for the preliminary screening of the target user information to narrow the selection range of the evaluation personnel. Then, according to the above-mentioned project scale level, the above-mentioned target user information set is preliminarily screened to obtain the screened target user information set as the candidate user information set. In order to narrow the selection range, a more accurate evaluation personnel can be selected later. Next, the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set are obtained from the target user database to obtain the first-level user academic feature information set group and the user introduction information set. Here, by obtaining the first-level user academic feature information set and the user introduction information corresponding to each user information, it is convenient to further narrow the user selection range through some characteristic information of the user in the subsequent process. Further, according to the user introduction information set, the second-level user academic feature information set corresponding to each candidate user information in the candidate user information set is generated to obtain the second-level user academic feature information set group. Here, through the user introduction information, some second-level user academic feature information for the corresponding candidate user information can be determined, so as to facilitate the subsequent comprehensive screening of the evaluators who can finally participate in the evaluation project according to the user academic feature information. Next, the first-level user academic feature information set group and the second-level user academic feature information set group are subjected to feature information fusion to obtain the fused user academic feature information set group. Furthermore, according to the fused user academic feature information set group, the candidate user information in the candidate user information set that can participate in the corresponding evaluation task of the above-mentioned project to be evaluated can be accurately determined as the evaluation user information, and at least one evaluation user information is obtained. Finally, for each evaluation user information in the at least one evaluation user information, the customized project invitation text corresponding to the evaluation user information is sent to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information can confirm whether to participate in the evaluation task on the terminal device.Therefore, the present disclosure selects evaluators according to the overall situation of the project and the personnel situation in the personnel information database, and can accurately determine at least one evaluator user who can participate in the above-mentioned evaluation task.

[0112] Further references Figure 2 As an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of a text sending device, and these device embodiments are Figure 1 Corresponding to the method embodiments shown, the text sending device can be specifically applied to various electronic devices.

[0113] like Figure 2 As shown, a text sending device 200 includes: a first acquisition unit 201, a first determination unit 202, a screening unit 203, a second acquisition unit 204, a generation unit 205, a fusion unit 206, a second determination unit 207 and a sending unit 208. Among them, the first acquisition unit 201 is configured to obtain the project to be evaluated and the target user database, wherein the above-mentioned target user database stores the user information of each target user information in the target user information set; the first determination unit 202 is configured to determine the project scale level of the above-mentioned project to be evaluated according to the project category, project number and project estimated value information of the above-mentioned project to be evaluated; the screening unit 203 is configured to screen the above-mentioned target user information set according to the above-mentioned project scale level, and obtain the screened target user information set as the candidate user information set; the second acquisition unit 204 is configured to obtain the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the above-mentioned candidate user information set from the above-mentioned target user database, and obtain the first-level user academic feature information set group and the user introduction information set; the generation unit 205 is configured to generate the above-mentioned candidate user information set according to the above-mentioned user introduction information set. A secondary user academic feature information set corresponding to each candidate user information in the user information set is selected to obtain a secondary user academic feature information set group; a fusion unit 206 is configured to fuse feature information of the above-mentioned primary user academic feature information set group with the above-mentioned secondary user academic feature information set group to obtain a fused user academic feature information set group; a second determination unit 207 is configured to determine, based on the above-mentioned fused user academic feature information set group, the candidate user information in the above-mentioned candidate user information set that can participate in the evaluation task corresponding to the above-mentioned project to be evaluated as the evaluation user information, to obtain at least one evaluation user information; a sending unit 208 is configured to, for each evaluation user information in the above-mentioned at least one evaluation user information, send the customized project invitation text corresponding to the above-mentioned evaluation user information to the terminal device corresponding to the above-mentioned evaluation user information, so that the evaluation user corresponding to the above-mentioned evaluation user information can confirm whether to participate in the above-mentioned evaluation task on the terminal device.

[0114] It is understandable that the units described in the text sending device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the method are also applicable to the text sending device 200 and the units included therein, and will not be described in detail here.

[0115] Reference below Figure 3 , which shows a structural schematic diagram of an electronic device (eg, an electronic device) 300 suitable for implementing some embodiments of the present disclosure. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0116] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0117] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0118] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0119] It should be noted that the computer-readable medium in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0120] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0121] The above-mentioned computer-readable medium may be included in the above-mentioned electronic device; or it may exist independently without being assembled into the electronic device. The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the electronic device, the electronic device: obtains the project to be evaluated and the target user database, wherein the above-mentioned target user database stores the user data of each target user information in the target user information set; determines the project scale level of the above-mentioned project to be evaluated according to the project category, project number and project estimated value information of the above-mentioned project to be evaluated; screens the above-mentioned target user information set according to the above-mentioned project scale level, and obtains the screened target user information set as the candidate user information set; obtains the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the above-mentioned candidate user information set from the above-mentioned target user database, and obtains the first-level user academic feature information set group and the user introduction information set; and screens the above-mentioned user information according to the above-mentioned user introduction. Information set, generate a secondary user academic feature information set corresponding to each candidate user information in the above candidate user information set, and obtain a secondary user academic feature information set group; fuse the feature information of the above primary user academic feature information set group with the above secondary user academic feature information set group, and obtain a fused user academic feature information set group; according to the above fused user academic feature information set group, determine the candidate user information in the above candidate user information set that can participate in the evaluation task corresponding to the above project to be evaluated as the evaluation user information, and obtain at least one evaluation user information; for each evaluation user information in the above at least one evaluation user information, send the customized project invitation text corresponding to the above evaluation user information to the terminal device corresponding to the above evaluation user information, so that the evaluation user corresponding to the above evaluation user information can confirm whether to participate in the above evaluation task on the terminal device.

[0122] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0123] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0124] The units described in some embodiments of the present disclosure may be implemented by software or by hardware. The described units may also be provided in a processor, for example, may be described as: a processor including a first acquisition unit, a first determination unit, a screening unit, a second acquisition unit, a generation unit, a fusion unit, a second determination unit, and a sending unit. The names of these units do not, in some cases, constitute limitations on the units themselves, for example, the first acquisition unit may also be described as a "unit for acquiring items to be evaluated and a target user database".

[0125] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0126] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A text sending method, comprising: Acquire a project to be evaluated and a target user database, wherein the target user database stores user data of each target user information in the target user information set; Determine the project scale level of the project to be evaluated based on the project category, project number and project estimated value information of the project to be evaluated; According to the project scale level, the target user information set is screened to obtain a screened target user information set as a candidate user information set; Acquire the primary user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set from the target user database to obtain a primary user academic feature information set group and a user introduction information set; According to the user introduction information set, a secondary user academic feature information set corresponding to each candidate user information in the candidate user information set is generated to obtain a secondary user academic feature information set group; The first-level user academic feature information set group and the second-level user academic feature information set group are subjected to feature information fusion to obtain a fused user academic feature information set group, wherein: The step of fusing the first-level user academic feature information set group with the second-level user academic feature information set group to obtain a fused user academic feature information set group includes: For each first-level user academic feature information in the first-level user academic feature information set, a first key-value pair generation step is performed: Setting the information weight corresponding to the first-level user academic characteristic information to a first value; Using the first-level user academic characteristic information as a value and the first numerical value as a key, generating a first key-value pair for the first-level user academic characteristic information; For each secondary user academic feature information in the secondary user academic feature information set, a second key-value pair generation step is performed: The information weight corresponding to the academic characteristic information of the secondary user is set to a second value, wherein the sum of the first value and the second value is 1, and the first value is greater than the second value; Using the secondary user academic characteristic information as a value and the second numerical value as a key, generating a second key-value pair for the secondary user academic characteristic information; For each candidate user information in the candidate user information set, perform the information generation step: Combining the first key-value pair and the second key-value pair corresponding to the candidate user information to obtain a combined key-value pair as the fused user academic feature information; According to the fused user academic feature information set group, candidate user information that can participate in the evaluation task corresponding to the project to be evaluated is determined in the candidate user information set as evaluation user information, and at least one evaluation user information is obtained, wherein: The step of determining, according to the fused user academic feature information set group, candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the project to be evaluated as evaluation user information, and obtaining at least one evaluation user information includes: For each fused user academic feature information in the fused user academic feature information set, a polygon graph generation step is performed: Encoding the primary user academic feature information in the first key-value pair included in the fused user academic feature information to obtain an information encoding vector; Multiplying the information encoding vector by the first value to obtain a first multiplied vector; Determine the word vector corresponding to the secondary user academic feature information in the second key-value pair included in the fused user academic feature information; Multiplying the word vector by the second value to obtain a second multiplied vector; Splicing the first multiplied vector and the second multiplied vector to obtain a spliced ​​vector; Input the splicing vector into a second multi-head attention mechanism network model to obtain a second weight set, wherein the second weight represents the degree of correlation between the splicing vector and each preset user academic ability information; Generating a user capability polygon graph for each preset user academic capability information according to the second weight set; According to the user capability polygon graph corresponding to each candidate user information in the candidate user information set, determine the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the project to be evaluated as the evaluation user information, and obtain at least one evaluation user information; For each evaluation user information in the at least one evaluation user information, the customized project invitation text corresponding to the evaluation user information is sent to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information can confirm whether to participate in the evaluation task on the terminal device.

2. The method according to claim 1, wherein: The target user information set is screened according to the project scale level to obtain a screened target user information set as a candidate user information set, including: Determining user screening area information for the project to be evaluated according to the project scale level; Acquire the address information of each target user information in the target user information set from the target user database; Remove target user information whose address information corresponds to an address not located in the area corresponding to the user screening area information from the target user information set, to obtain a first target user information set after removal; Acquire nucleic acid detection information of each target user information in the first removed target user information set from the target user database; The target user information whose corresponding nucleic acid test information is not tested for nucleic acid or whose nucleic acid test result is positive is removed from the first removed target user information set to obtain a second removed target user information set as the candidate user information set.

3. The method according to claim 2, wherein: The step of generating a secondary user academic feature information set corresponding to each candidate user information in the candidate user information set according to the user introduction information set comprises: For each user introduction information in the user introduction information set, the following information generation steps are performed: Performing word segmentation processing on the user introduction information to obtain a word set; Removing words whose part-of-speech categories are the target category from the word set to obtain a first removed word set; Get the preset user academic feature information table; Performing word encoding on each word in the first removed word set to obtain a word vector set; Encoding each user academic feature information included in the user academic feature information table to obtain a coding vector set; For each word vector in the word vector set, determining a vector distance between the word vector and each encoding vector in the encoding vector set; Removing words whose corresponding vector distances are greater than the target distance from the first removed word set to obtain a second removed word set; Inputting the second removed word set and the academic feature information of each user into a multi-head attention mechanism network model to obtain a first weight set, wherein the first weight represents the degree of correlation between the user academic feature information and the words in the second removed word set; According to the first weight set, at least one word is removed from the second removed word set to obtain a third removed word set as the secondary user academic feature information set.

4. The method according to claim 1, wherein: The method further comprises: In response to receiving participation information sent by each evaluation user information in the at least one evaluation user information, and the participation information represents the evaluation user's participation in the evaluation task, generating a task participant list text for the evaluation task; Sending the task participant list text to the review end to review the at least one evaluation user information; In response to the at least one evaluation user information being approved, a list of required materials representing participation in the evaluation task is sent to a terminal device corresponding to each evaluation user.

5. The method according to claim 4, wherein: The audit end audits the at least one evaluation user information by the following steps: Obtain an evaluation user information set for each historical evaluation project in the historical evaluation project set to obtain an evaluation user information set group; For each evaluation user information set in the evaluation user information set group, determining the number of evaluation user information that is identical between the evaluation user information set and the at least one evaluation user information; Filter out historical evaluation items whose corresponding number is greater than a predetermined value from the historical evaluation item set as comparative evaluation items to obtain a comparative evaluation item set; In response to determining that there is a corresponding project in the comparison and evaluation project set whose start time is greater than the project start time of the project to be evaluated than the predetermined time period, it is determined that the at least one evaluation user information is approved.

6. A text sending device, comprising: A first acquisition unit is configured to acquire a project to be evaluated and a target user database, wherein the target user database stores user data of each target user information in the target user information set; A first determining unit is configured to determine the project scale level of the project to be evaluated according to the project category, project staff and project estimated value information of the project to be evaluated; A screening unit is configured to screen the target user information set according to the project scale level to obtain a screened target user information set as a candidate user information set; The second acquisition unit is configured to acquire the first-level user academic feature information set and user introduction information corresponding to each candidate user information in the candidate user information set from the target user database to obtain a first-level user academic feature information set group and a user introduction information set; A generating unit is configured to generate a secondary user academic feature information set corresponding to each candidate user information in the candidate user information set according to the user introduction information set, so as to obtain a secondary user academic feature information set group; A fusion unit is configured to fuse the feature information of the first-level user academic feature information set group with the second-level user academic feature information set group to obtain a fused user academic feature information set group, wherein the fusion of the feature information of the first-level user academic feature information set group with the second-level user academic feature information set group to obtain a fused user academic feature information set group includes: for each first-level user academic feature information in the first-level user academic feature information set group, executing a first key-value pair generation step: setting the information weight corresponding to the first-level user academic feature information to a first value; using the first-level user academic feature information as a value and the first value as a key, generating a first key-value pair for the first-level user academic feature information; key-value pair; for each secondary user academic feature information in the secondary user academic feature information set group, execute a second key-value pair generation step: set the information weight corresponding to the secondary user academic feature information to a second numerical value, wherein the sum of the first numerical value and the second numerical value is 1, and the first numerical value is greater than the second numerical value; take the secondary user academic feature information as the value and the second numerical value as the key to generate a second key-value pair for the secondary user academic feature information; for each candidate user information in the candidate user information set, execute an information generation step: perform a key-value pair combination on the first key-value pair and the second key-value pair corresponding to the candidate user information to obtain a combined key-value pair as the fused user academic feature information; The second determination unit is configured to determine, based on the fused user academic feature information set group, the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the project to be evaluated, as the evaluation user information, to obtain at least one evaluation user information, wherein, based on the fused user academic feature information set group, determining, as the evaluation user information, the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the project to be evaluated, to obtain at least one evaluation user information, comprises: for each fused user academic feature information in the fused user academic feature information set group, executing a polygonal graph generation step: encoding the primary user academic feature information in the first key-value pair included in the fused user academic feature information to obtain an information encoding vector; multiplying the information encoding vector by the first numerical value to obtain a first multiplication vector quantity; determine the word vector corresponding to the secondary user academic feature information in the second key-value pair included in the fused user academic feature information; multiply the word vector by the second value to obtain a second multiplied vector; concatenate the first multiplied vector and the second multiplied vector to obtain a concatenated vector; input the concatenated vector into a second multi-head attention mechanism network model to obtain a second weight set, wherein the second weight represents the degree of association between the concatenated vector and each preset user academic ability information; based on the second weight set, generate a user ability polygon graph for each preset user academic ability information; based on the user ability polygon graph corresponding to each candidate user information in the candidate user information set, determine the candidate user information in the candidate user information set that can participate in the evaluation task corresponding to the project to be evaluated as the evaluation user information, and obtain at least one evaluation user information; The sending unit is configured to send the customized project invitation text corresponding to each evaluation user information in the at least one evaluation user information to the terminal device corresponding to the evaluation user information, so that the evaluation user corresponding to the evaluation user information can confirm whether to participate in the evaluation task on the terminal device.

7. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

8. A computer readable medium having a computer program stored thereon, wherein: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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