An online testing method, system and terminal for logo splitting

Abstract

The present invention is applicable to the field of online testing technologies, and particularly relates to a method, a system and a terminal for online testing of logo clones. The method includes: S100: Obtain evaluations of logo clones on a preset platform, synchronize a preset number of evaluations to nodes that have been created, establish an emotion dictionary, where the emotion dictionary at least includes: emotion words and scores, and based on the emotion words, determine the scores of each evaluation; S200: Arrange the scores, find the first quartile, the median and the third quartile in the scores, and denote them as Q1, Q2 and Q3 respectively, and denote the interquartile range as IQR, find the outliers and delete them. By generating a compensation coefficient, the present invention can correct the remaining part of the available evaluations, expand the sources of evaluations, balance the data impact, and maintain data integrity. By constructing a linked list, the present invention can record user evaluations and version changes, so as to better track the design evolution and provide decision support for the modification of logo clones.

Description

Technical Field

[0001] The present invention relates to the technical field of online testing, and particularly to a method, a system and a terminal for online testing of logo clones. Background Art

[0002] A logo clone refers to the use of the same brand logo in different places, which is usually used for brand promotion. Brand owners will adjust the color matching, borders, etc. of the logo according to time, seasons, holidays or specific events. For example, some brand owners will adjust the logo to rainbow color matching on their anniversary to create an event atmosphere and enhance team cohesion.

[0003] In actual use, for such logo clones, online testing is required after creation to obtain public feedback for adjusting the logo clones, avoiding potential problems and improving the recognition of the logo. Therefore, "how to identify potential problems and store the entire creation process" is the technical problem to be solved by the present invention. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, a system and a terminal for online testing of logo clones to solve the problem of "how to identify potential problems and store the entire creation process" raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A method for online testing of logo clones, the method comprising:

[0007] S100: Obtain evaluations of logo clones on a preset platform, synchronize a preset number of evaluations to the created nodes, establish an emotion dictionary, where the emotion dictionary at least includes: emotion words and scores, and determine the score of each evaluation based on the emotion words;

[0008] S200: Arrange the scores, find the first quartile, median and third quartile in the scores, and denote them as Q 1 、Q 2 and Q 3 , denote the interquartile range as IQR, find the outliers and delete them;

[0009] S300: Represent the evaluations with scores less than Q 1 with 00, the evaluations between Q 1 -Q 2 with 01, the evaluations between Q 2 -Q 3 with 10, and the evaluations greater than Q 3The evaluation is represented by 11, a unique identifier is generated, and the evaluation in the node is replaced, and the evaluation is inserted by Q 1 , Q 2 and Q 3 Generated tags;

[0010] S400: The score is set in Q 1 and Q 3 The evaluations between the nodes are defined as available evaluations, the features of the available evaluations are extracted, the modification parts and suggestions are determined, the remaining evaluations in the node are determined as extreme evaluations, the user IDs of the extreme evaluations are traversed, a historical evaluation data set is created, the evaluation scale of each user ID is located, a compensation coefficient is generated, and the scores of the extreme evaluations are corrected by using the compensation coefficients, the scores of the extreme evaluations are rearranged, S200 and S300 are repeated, and the features are updated;

[0011] S500: Determine the version of the logo clone, establish a correspondence between a node and the version, link all nodes, generate a linked list, and output the modified part and the suggestion, wherein the linked list is used to represent the version change of the logo clone;

[0012] S600: Integrate a side chain into the linked list, set a point parallel to the node, and build a coordinated link between the point and the node, wherein the side chain is used to represent several versions of the logo clone.

[0013] Furthermore, the S100 includes:

[0014] Determine the number of logo clone versions that need to be tested, and if the number is "1", directly assign the logo clone to the node;

[0015] If the number is greater than "1", trace back to the source of the logo clone, and determine the primary version and secondary version based on the creative intention of the source;

[0016] The major version and the minor version are uploaded to a pre-selected test platform.

[0017] Furthermore, the S100 further includes:

[0018] Collecting the evaluations in the test platform, importing the evaluations of the primary version into the node, transferring the evaluations of the secondary version into the point position, and linking the nodes and the point position using the overall link;

[0019] Locate the user ID that posted the review, unify the format of the review, and divide it into words, query the sentiment dictionary, determine the score of each word, and add them up to get the score of the review;

[0020] Extract the sentence patterns in the evaluation and adjust the score using the scores of the sentence patterns.

[0021] Further, the S200 includes:

[0022] Build a data processing pipeline between the node and the test platform, and generate a data stream when a new evaluation is generated.

[0023] Arrange the scores in ascending order and determine Q 1 、Q 2 and Q 3 , and via the data processing channel, perform dynamic updates using the data stream.

[0024] Define the difference between Q 3 and Q 1 as the interquartile range (IQR), delete the outliers in the sorted result, where the score of the outlier is greater than Q 3 + 1.5×IQR or less than Q 1 - 1.5×IQR.

[0025] Further, the S400 includes:

[0026] Split the evaluation into available evaluations and extreme evaluations, and create directories for each respectively.

[0027] Build a mapping relationship between the unique identifier, the evaluation, and the feature, and transfer the unique identifier and the mapping relationship into the node.

[0028] Extract the modified parts and suggestions in the feature and sort them according to the number of occurrences.

[0029] Further, the S500 includes:

[0030] Determine the version of the logo clone, where the version includes at least a first version, a second version, and a third version, and build nodes with the same number as the number of versions, where the nodes include at least a first node, a second node, and a third node;

[0031] Based on the corresponding relationship, classify the first version into the first node, and so on;

[0032] Integrate all the nodes to generate a linked list, and insert pointers into the linked list, where the pointers are from the first node to the second node.

[0033] Further, the S600 includes:

[0034] Integrate side chains with the same number as the number of sub - versions into the linked list. Based on the creative intention, synchronize the main version into the nodes and transfer the sub - version into the points.

[0035] Based on the overall link, determine the evaluation sharing strategy between the linked list and the side chain.

[0036] Further, the method further includes:

[0037] Locate the tail and head of the linked list. In the tail, mark the root node for overall coordinating all nodes and points. In the head, mark the output node, and the output node integrates a storage mechanism;

[0038] Delete the empty points in the side chain, and use the storage mechanism to store the versions of the logo avatars in the linked list and the side chain.

[0039] Further, the system includes:

[0040] A determination module, configured to obtain evaluations of the logo avatar of a preset platform, synchronize a preset number of evaluations to the created nodes, and establish an emotion dictionary, where the emotion dictionary at least includes: emotion words and scores, and based on the emotion words, determine the scores of each evaluation;

[0041] A search module, configured to arrange the scores, find the first quartile, median, and third quartile in the scores, and denote them as Q 1 、Q 2 and Q 3 , and denote the interquartile range as IQR, find the outliers and delete them;

[0042] An insertion module, configured to represent the evaluations with scores less than Q 1 with 00, the evaluations between Q 1 -Q 2 with 01, the evaluations between Q 2 -Q 3 with 10, and the evaluations greater than Q 3 with 11, generate a unique identifier, and replace the evaluations in the nodes, and insert the label generated by Q 1 、Q 2 and Q 3 ;

[0043] An update module, configured to define the evaluations with scores between Q 1 and Q 3 as available evaluations, extract the features of the available evaluations, determine the modified parts and suggestions, determine the remaining evaluations in the nodes as extreme evaluations, traverse the user IDs of the extreme evaluations, create a historical evaluation dataset, locate the evaluation scales of each user ID, generate a compensation coefficient, and use the compensation coefficient to correct the scores of the extreme evaluations, rearrange the scores of the extreme evaluations, repeat S200 and S300, and update the features;

[0044] An output module, configured to determine the version of the logo clone, establish the correspondence between nodes and the version, link all the nodes to generate a linked list, and output the modified part and suggestions, wherein the linked list is used to represent the version change of the logo clone;

[0045] A building module, configured to integrate a side chain into the linked list, set points parallel to the nodes, and build an overall link between the points and the nodes, wherein the side chain is used to represent several versions of the logo clone.

[0046] Furthermore, a terminal stores at least one program code, and the program code is loaded and executed by a processor to implement the online testing method of the logo clone.

[0047] Compared with the prior art, the beneficial effects of the present invention are:

[0048] 1. By obtaining user evaluations, market verification can be carried out, and the logo clone can be better improved, enhancing the user's sense of participation. By determining scores, quantitative feedback can be provided, facilitating the tracking of improvement effects and improving the user experience. By generating unique identifiers, data processing can be simplified, storage space can be saved, and at the same time, the testing efficiency of the logo clone can be greatly improved. By determining available evaluations, the representativeness of the evaluations can be greatly improved, biases can be reduced, and the effectiveness of data analysis can be enhanced. By generating a compensation coefficient, the remaining part of the available evaluations can be corrected, the source of the evaluations can be expanded, the data impact can be balanced, and data integrity can be maintained. By constructing a linked list, user evaluations and version changes can be recorded, so as to better track the design evolution and provide decision support for the modification of the logo clone.

[0049] 2. By constructing a side chain and a storage mechanism, online testing of multiple versions of the logo clone can be carried out simultaneously, greatly improving the testing efficiency and effectively ensuring the integrity of the testing. Description of the Drawings

[0050] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0051] Figure 1 It is a flow block diagram of the online testing method of the logo clone provided by the embodiment of the present invention;

[0052] Figure 2 It is the first sub-flow block diagram of the online testing method of the logo clone provided by the embodiment of the present invention;

[0053] Figure 3It is the second sub - process block diagram of the online testing method for logo cloning provided by the embodiment of the present invention;

[0054] Figure 4 It is the fourth sub - process block diagram of the online testing method for logo cloning provided by the embodiment of the present invention;

[0055] Figure 5 It is the fifth sub - process block diagram of the online testing method for logo cloning provided by the embodiment of the present invention;

[0056] Figure 6 It is the sixth sub - process block diagram of the online testing method for logo cloning provided by the embodiment of the present invention;

[0057] Figure 7 It is the block diagram of the composition of the online testing system for logo cloning provided by the embodiment of the present invention;

[0058] Figure 8 It is the block diagram of the composition of the determination module in the online testing system for logo cloning provided by the embodiment of the present invention;

[0059] Figure 9 It is the block diagram of the composition of the search module in the online testing system for logo cloning provided by the embodiment of the present invention;

[0060] Figure 10 It is the block diagram of the composition of the update module in the online testing system for logo cloning provided by the embodiment of the present invention;

[0061] Figure 11 It is the block diagram of the composition of the output module in the online testing system for logo cloning provided by the embodiment of the present invention;

[0062] Figure 12 It is the block diagram of the composition of the building module in the online testing system for logo cloning provided by the embodiment of the present invention. Detailed implementation manners

[0063] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0064] In Embodiment 1, Figure 1 The implementation process of the online testing method for logo cloning provided by the embodiment of the present invention is shown, and the details are as follows:

[0065] S100: Obtain the evaluation of the logo clone of the preset platform, synchronize a preset number of evaluations to the created nodes, establish an emotion dictionary, where the emotion dictionary at least includes: emotion words and scores, and determine the score of each evaluation based on the emotion words.

[0066] Obtain the evaluations of the user on the logo avatar in a preset platform, where the preset platform can be a forum, a designer sharing platform, a Tieba, etc., and select a preset number of evaluations from them (the preset number is not limited), and synchronize these evaluations to the node. Establish an emotion dictionary, which includes an unlimited number of emotion words and corresponding scores; for example, the score of the emotion word "good" can be 1 point, "bad" is -1 point, and "very good" is 3 points. Determine the score of each evaluation by retrieving the emotion words in each evaluation.

[0067] S200: Arrange the scores, find the first quartile, median, and third quartile in the scores, and denote them as Q 1 、Q 2 and Q 3 , and denote the interquartile range as IQR, find the outliers and delete them.

[0068] After determining the score of each evaluation, arrange the evaluations in ascending order of score, find the first quartile, median, and third quartile in the scores; and determine the outliers in the scores and delete these outliers. Here, the outliers are extreme evaluations, and the meaning of extreme evaluations is evaluations with prejudice, aggression, or being unrealistic.

[0069] S300: Represent the evaluations with scores less than Q 1 with 00, the evaluations between Q 1 -Q 2 with 01, the evaluations between Q 2 -Q 3 with 10, and the evaluations greater than Q 3 with 11, generate a unique identifier, and replace the evaluations in the node, and insert the label generated by Q 1 、Q 2 and Q 3 .

[0070] Generate a unique identifier according to the score of the evaluation. By querying the unique identifier, the evaluation situation of the user on the logo avatar can be mastered. The advantage of doing this is that when storing the logo avatar version, the data storage volume can be reduced; delete the evaluations in the node, transfer the unique identifier to the node, and at the same time insert the label generated by Q 1 、Q 2 and Q 3 into the node. The above user is a user registered in the preset platform.

[0071] S400: For the scores between Q 1 and Q 3The evaluations between are defined as available evaluations. Extract the features of the available evaluations, determine the modified parts and suggestions, determine the remaining evaluations in the nodes as extreme evaluations, traverse the user IDs of the extreme evaluations, create a historical evaluation dataset, locate the evaluation scales of each user ID, generate compensation coefficients, and use the compensation coefficients to correct the scores of the extreme evaluations, rearrange the scores of the extreme evaluations, repeat S200 and S300, and update the features.

[0072] Define the evaluations with scores between Q 1 and Q 3 as available evaluations, and find the features in the available evaluations. The features are the parts that need to be modified in the logo clone versions proposed by users in the available evaluations, and the features also include modification suggestions, etc.; determine the remaining evaluations in the nodes, that is, the evaluations with scores less than Q 1 or scores greater than Q 3 as extreme evaluations, trace the user IDs in the preset platform, create a historical evaluation dataset for each of the user IDs, determine the evaluation scales of each user ID, and generate corresponding compensation coefficients.

[0073] In actual tests, find the user IDs corresponding to the extreme evaluations and establish a historical evaluation dataset, and judge whether the historical evaluations of these users are objective; by objective, it means whether the scores of the user's evaluations on other logo designs are between the corresponding Q 1 and Q 3 If so, it means that the user is relatively objective and a smaller compensation coefficient can be given. If not, it means that the user's evaluation style or scale is relatively special, and a larger compensation coefficient needs to be given.

[0074] Use the compensation coefficients to correct the scores of the extreme evaluations, and after correction, rearrange the scores of the extreme evaluations; it should be noted that at this time, the available evaluations do not participate in the arrangement. Find the evaluations of the extreme evaluations that are between Q 1 and Q 3 and extract the corresponding features.

[0075] S500: Determine the version of the logo clone, establish the corresponding relationship between the nodes and the version, link all the nodes to generate a linked list, and output the modified parts and suggestions, where the linked list is used to represent the version change of the logo clone.

[0076] Determine the version of the logo clone. In actual tests, the version design of the logo clone needs to go through multiple iterations. Transfer the evaluation of one version of the logo clone to a node, that is, one node stores the evaluation of one version of the logo clone. Link all the nodes to generate a linked list. By constructing the linked list, the entire creation process of the logo clone and the corresponding evaluations can be recorded, and at the same time, the modified parts and suggestions can be determined.

[0077] S600: Integrate a side chain into the linked list, set points parallel to the nodes, and build an overall link between the points and the nodes, where the side chain is used to represent several versions of the logo clone.

[0078] Insert a side chain into the linked list, where the side chain consists of several points. One node corresponds to one or more points, and the points and nodes are linked through an overall link.

[0079] In actual tests, the creator may create several versions of the logo clone simultaneously and release them to a preset platform at the same time so as to select the one with better feedback. At this time, it is necessary to determine the main version and the secondary version among them, transfer the evaluation data of the main version to the node, transfer the evaluation data of the secondary version to the point, and store all versions during the creation process. In addition, if there is only one version of the logo clone, there is no need to use points. At this time, the area parallel to the nodes in the side chain is an empty point.

[0080] In Embodiment 2, Figure 2 The implementation process of the online test method for the logo clone provided by the embodiment of the present invention is shown. The following details S100 as follows:

[0081] S101: Determine the number of versions of the logo clone to be tested. If the number is "1", directly classify the logo clone into the node.

[0082] Determine the number of versions of the logo clone. If the number of versions is 1, classify the logo clone into the node.

[0083] S102: If the number is greater than "1", trace back the source of the logo clone, and determine the main version and the secondary version based on the creative intention of the source.

[0084] If the number of versions is greater than 1, trace back the source of the logo clone, that is, find out the creator. According to the creative intention of the creator, determine the main version and the secondary version. The division of the main and secondary versions can be the preference degree of the creator. The division of the main and secondary versions is mainly to record and store the creation process of the logo clone in more detail.

[0085] S103: Upload the major version and the minor version to a pre-selected test platform.

[0086] Upload the major version and the minor version to the test platform, and collect the evaluations of users in the test platform.

[0087] In Embodiment 3, Figure 2 The implementation process of the logo split online testing method provided by the embodiment of the present invention is shown. The following details S100 in detail as follows:

[0088] S104: Collect the evaluations in the test platform, import the evaluations of the major version into the nodes, transfer the evaluations of the minor version into the points, and use the overall planning link to link the nodes and the points.

[0089] Transfer the evaluations of the major version and the minor version into the nodes and the points respectively, and at the same time establish an overall planning link between the nodes and the points. The overall planning link is mainly used for evaluation data exchange and coordination between the nodes and the points.

[0090] For example, in the platform, name the major version as A and the minor version as B. If a user mentions in the evaluation that "A is not as good as B", then through the overall planning link, query the sentiment dictionary to determine the scores of this evaluation in the node corresponding to A and the point corresponding to B.

[0091] S105: Locate the user ID that published the evaluation, unify the format of the evaluation, split it into words, query the sentiment dictionary, determine the score of each word, and superimpose to obtain the score of the evaluation.

[0092] Use the user ID as an attribute of the evaluation to determine the format of the evaluation. The format can be subject + predicate + object, etc. Delete the useless words such as the subject and labels, split the evaluation into several words, query the sentiment dictionary to determine the score of each word, and obtain the score of the evaluation by superimposing.

[0093] S106: Extract the sentence pattern in the evaluation, and adjust the score using the score of the sentence pattern.

[0094] In addition to the scores, the sentiment dictionary should also include sentence patterns, and each sentence pattern also corresponds to a score. Use the score of the sentence pattern to correct the score of the evaluation.

[0095] In Embodiment 4, Figure 3 The implementation process of the logo split online testing method provided by the embodiment of the present invention is shown. The following details S200 in detail as follows:

[0096] S201: Build a data processing pipeline between the node and the test platform. When a new evaluation is generated, generate a data stream.

[0097] Build a data processing pipeline between the nodes and the test platform. When a new evaluation is generated, generate a data stream and use this data stream to dynamically adjust the scores.

[0098] S202: Arrange the scores in ascending order and determine Q 1 、Q 2 and Q 3 , and via the data processing channel, perform dynamic updates using the data stream.

[0099] Arrange the collected scores in ascending order and determine Q 1 、Q 2 and Q 3 . When a new evaluation is generated, use the data stream to dynamically update the arrangement result.

[0100] S203: Define the difference between Q 3 and Q 1 as the interquartile range (IQR), and delete the outliers in the arrangement result. The scores of the outliers are greater than Q 3 + 1.5×IQR or less than Q 1 - 1.5×IQR.

[0101] Define the difference between Q 3 and Q 1 as the interquartile range, denoted by IQR. Define the evaluations with scores greater than Q 3 + 1.5×IQR and scores less than Q 1 - 1.5×IQR as outliers, and delete the outliers in the arrangement result; by deleting outliers, extreme evaluations in the evaluations can be reduced, bias can be lowered, and data authenticity can be improved.

[0102] In Embodiment 5, Figure 4 shows the implementation process of the logo clone online test method provided by the embodiment of the present invention. The following details S400 as follows:

[0103] S401: Split the evaluation into available evaluations and extreme evaluations, and create directories respectively.

[0104] Split the user's evaluation into available evaluations and extreme evaluations, and create a directory of sentiment words. By locating the sentiment words in the evaluation and querying the directory, the score of the evaluation can be determined.

[0105] S402: Build a mapping relationship between the unique identifier, the evaluation, and the feature, and transfer the unique identifier and the mapping relationship into the node.

[0106] Establish a mapping relationship between the unique identifier, the evaluation, and the feature. By establishing the mapping relationship, the corresponding evaluation and feature can be located according to the unique identifier, which is convenient for the subsequent processing of user evaluations.

[0107] S403: Extract the modified parts and suggestions in the features and sort them according to the number of occurrences.

[0108] Among numerous evaluations, the same or similar modified parts and suggestions will surely appear. Sort them according to the number of occurrences of the modified parts and suggestions, and give priority to processing the modified parts ranked among the top in terms of the number of occurrences.

[0109] In Embodiment 6, Figure 5 The implementation process of the logo split-screen online testing method provided by the embodiment of the present invention is shown. The following details S500 as follows:

[0110] S501: Determine the version of the logo split-screen, where the version includes at least a first version, a second version, and a third version, and construct nodes with the same number as the number of versions. The nodes include at least a first node, a second node, and a third node.

[0111] In actual creation, the logo split-screen into a version will surely go through several version iterations. According to the iteration order, determine the first version, the second version, and the third version, and construct nodes with the same number as the number of versions. Each node stores the evaluation of one version.

[0112] S502: Based on the corresponding relationship, classify the first version into the first node, and so on.

[0113] Via the corresponding relationship, classify the logo split-screen and evaluation in the first version into the first node, classify the logo split-screen and evaluation in the second version into the second node, and so on.

[0114] S503: Integrate all the nodes to generate a linked list, and insert pointers into the linked list. The pointer is from the first node to the second node.

[0115] Integrate all the nodes to generate a linked list, and insert pointers between the first node and the second node, the second node and the third node, and so on; by inserting pointers, the creation process of the logo split-screen version can be more intuitively displayed.

[0116] In Embodiment 7, Figure 6 The implementation process of the logo split-screen online testing method provided by the embodiment of the present invention is shown. The following details S600 as follows:

[0117] S601: Integrate side chains with the same number as the number of sub-versions into the linked list. Based on the creation intention, synchronize the main version into the nodes and transfer the sub-versions into the points.

[0118] Integrate side chains into the linked list, where the side chains are used to test the sub-versions of the logo clones, and construct the same number of side chains as the number of sub-versions.

[0119] In actual creation, multiple logo clones may be created simultaneously and uploaded to the platform for users to evaluate. Each logo clone version has its own independent creation path, and the side chains are used to record and store the creation process of each sub-version.

[0120] S602: Based on the overall link, determine the evaluation sharing strategy between the linked list and the side chains.

[0121] Use the overall link to determine the evaluation sharing strategy between the linked list and the side chains. The evaluation sharing strategy is that a certain evaluation mentioned above involves both the main version and the sub-versions at the same time, and determine the scores of this evaluation in the main version and the sub-versions.

[0122] In Example 8, different from Example 1, in the embodiment of the present invention, the method further includes:

[0123] Locate the tail and head of the linked list. In the tail, mark the root node for overall planning of all nodes and points. In the head, mark the output node, and a storage mechanism is integrated in the output node;

[0124] Delete the empty points in the side chains, and use the storage mechanism to store the versions of the logo clones in the linked list and the side chains.

[0125] Determine the tail and head of the linked list. Insert the root node at the tail of the linked list, where the root node is used for overall planning and management of all nodes and points to avoid version confusion and test anomalies; insert the output node at the head of the linked list, and at the same time integrate a storage mechanism into the output node. The storage mechanism stores the unique identifier, mapping relationship, Q 1 、Q 2 、Q 3 、modified parts and suggestions, etc. in the order of logo clone version iteration.

[0126] During the storage process, it is necessary to delete the empty points in the side chains; for example, when initially evaluating the logo clone version, the creator uploads 1 main version and 3 sub-versions of the logo clone to the preset platform, transfers the main version into the nodes in the linked list, and transfers the sub-versions into the points parallel to the nodes; during the continuous creation process, the creator deletes 2 of the sub-versions, and in the side chains corresponding to these 2 sub-versions, the next points pointed to by the points storing the logo clone versions of these 2 sub-versions are empty points because there is no further creation.

[0127] Figure 7The composition structure block diagram of the logo clone online testing system provided by the embodiments of the present invention is shown. The logo clone online testing system 1 includes:

[0128] A determination module 11, configured to obtain evaluations of the logo clone of a preset platform, synchronize a preset number of evaluations to the created nodes, establish an emotion dictionary, where the emotion dictionary at least includes: emotion words and scores, and determine the score of each evaluation based on the emotion words;

[0129] A search module 12, configured to arrange the scores, find the first quartile, median, and third quartile in the scores, and record them as Q 1 、Q 2 and Q 3 respectively, record the interquartile range as IQR, find the outliers and delete them;

[0130] An insertion module 13, configured to represent the evaluations with scores less than Q 1 as 00, the evaluations between Q 1 -Q 2 as 01, the evaluations between Q 2 -Q 3 as 10, the evaluations greater than Q 3 as 11, generate a unique identifier, and replace the evaluations in the nodes, and insert the labels generated by Q 1 、Q 2 and Q 3 ;

[0131] An update module 14, configured to define the evaluations between Q 1 and Q 3 as available evaluations, extract the features of the available evaluations, determine the modified parts and suggestions, determine the remaining evaluations in the nodes as extreme evaluations, traverse the user IDs of the extreme evaluations, create a historical evaluation data set, locate the evaluation scales of each user ID, generate a compensation coefficient, and use the compensation coefficient to correct the scores of the extreme evaluations, rearrange the scores of the extreme evaluations, repeat S200 and S300, and update the features;

[0132] An output module 15, configured to determine the version of the logo clone, establish the correspondence between the nodes and the version, link all the nodes, generate a linked list, and output the modified parts and suggestions, where the linked list is used to represent the version changes of the logo clone;

[0133] A construction module 16, configured to integrate side chains into the linked list, set points parallel to the nodes, and construct the overall link between the points and the nodes, where the side chains are used to represent several versions of the logo clone.

[0134] Figure 8 The composition structure block diagram of the logo clone online testing system provided by the embodiment of the present invention is shown. The determination module 11 includes:

[0135] The classification unit 111 is used to determine the number of logo clones to be tested. If the number is "1", directly classify the logo clone into the node;

[0136] The backtracking unit 112 is used to backtrack the source of the logo clone when the number is greater than "1", and determine the main version and the secondary version based on the creative intention of the source;

[0137] The uploading unit 113 is used to upload the main version and the secondary version to a pre-selected testing platform;

[0138] The linking unit 114 is used to collect the evaluations in the testing platform, import the evaluations of the main version into the node, transfer the evaluations of the secondary version into the point position, and link the node and the point position using the overall link;

[0139] The superimposing unit 115 is used to locate the user ID who published the evaluation, unify the format of the evaluation, split it into words, query the sentiment dictionary, determine the score of each word, and superimpose to obtain the score of the evaluation;

[0140] The adjustment unit 116 is used to extract the sentence pattern in the evaluation and adjust the score using the score of the sentence pattern.

[0141] Figure 9 The composition structure block diagram of the logo clone online testing system provided by the embodiment of the present invention is shown. The searching module 12 includes:

[0142] The generating unit 121 is used to build the data processing pipeline between the node and the testing platform, and generate a data stream when a new evaluation is generated;

[0143] The updating unit 122 is used to arrange the scores in ascending order and determine Q 1 、Q 2 and Q 3 , and perform dynamic update using the data stream via the data processing channel;

[0144] The defining unit 123 is used to define the difference between Q 3 and Q 1 as the interquartile range, and delete the outliers in the sorting result, where the score of the outlier is greater than Q 3 +1.5×IQR or less than Q 1 -1.5×IQR.

[0145] Figure 10The block diagram of the composition structure of the logo split online test system provided by the embodiments of the present invention is shown. The update module 14 includes:

[0146] A creation unit 141, configured to split the evaluation into an available evaluation and an extreme evaluation, and create directories respectively;

[0147] A mapping unit 142, configured to build a mapping relationship between a unique identifier, an evaluation, and a feature, and transfer the unique identifier and the mapping relationship into a node;

[0148] A sorting unit 143, configured to extract the modified parts and suggestions in the feature, and sort them according to the number of occurrences.

[0149] Figure 11 The block diagram of the composition structure of the logo split online test system provided by the embodiments of the present invention is shown. The output module 15 includes:

[0150] A determination unit 151, configured to determine the version of the logo split, where the version includes at least a first version, a second version, and a third version, build nodes with the same number as the version number, and the nodes include at least a first node, a second node, and a third node;

[0151] A corresponding unit 152, configured to classify the logo split in the first version into the first node according to the corresponding relationship, and so on;

[0152] An integration unit 153, configured to integrate all nodes, generate a linked list, and insert a pointer into the linked list, where the pointer is from the first node to the second node.

[0153] Figure 12 The block diagram of the composition structure of the logo split online test system provided by the embodiments of the present invention is shown. The building module 16 includes:

[0154] A transfer-in unit 161, configured to integrate side chains with the same number as the secondary version number into the linked list, synchronize the main version to the nodes based on the creative intention, and transfer the secondary version to the positions;

[0155] A sharing unit 162, configured to determine an evaluation sharing strategy between the linked list and the side chains based on the overall link.

[0156] Among them, the determination module 11 is mainly used to complete step S100, the search module 12 is mainly used to complete step S200, the insertion module 13 is mainly used to complete step S300, the update module 14 is mainly used to complete step S400, the output module 15 is mainly used to complete step S500, and the building module 16 is mainly used to complete step S600;

[0157] The classification unit 111 is mainly used to complete step S101, the backtracking unit 112 is mainly used to complete step S102, the uploading unit 113 is mainly used to complete step S103, the linking unit 114 is mainly used to complete step S104, the overlaying unit 115 is mainly used to complete step S105, and the adjustment unit 116 is mainly used to complete step S106;

[0158] The generation unit 121 is mainly used to complete step S201, the update unit 122 is mainly used to complete step S202, and the definition unit 123 is mainly used to complete step S203;

[0159] The creation unit 141 is mainly used to complete step S401, the mapping unit 142 is mainly used to complete step S402, and the sorting unit 143 is mainly used to complete step S403;

[0160] The determination unit 151 is mainly used to complete step S501, the corresponding unit 152 is mainly used to complete step S502, and the integration unit 153 is mainly used to complete step S503;

[0161] The transfer unit 161 is mainly used to complete step S602, and the sharing unit 162 is mainly used to complete step S602;

[0162] All functions that can be achieved by the described logo clone online testing method are completed by a computer device. The computer device includes one or more processors and one or more memories. At least one program code is stored in the one or more memories, and the program code is loaded and executed by the one or more processors to implement the functions of the logo clone online testing method.

[0163] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0164] The above-described embodiments only represent several implementation manners of the present invention. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be subject to the appended claims.

[0165] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A logo clone online testing method, characterized in that: The method comprises: S100: obtaining evaluations of logo avatars of a preset platform, and synchronizing a preset number of evaluations to the created nodes, and establishing a sentiment dictionary, wherein the sentiment dictionary at least includes: sentiment words and scores, and determining the score of each evaluation based on the sentiment words; S200: Arrange the scores, find the first quartile, median and third quartile of the scores, and record them as Q1, Q2 and Q3 respectively, record the interquartile range as IQR, find out the outliers and delete them; S300: The evaluation with a score less than Q1 is represented by 00, the evaluation between Q1 and Q2 is represented by 01, the evaluation between Q2 and Q3 is represented by 10, and the evaluation greater than Q3 is represented by 11, a unique identifier is generated, and the evaluation in the node is replaced, and a label generated by Q1, Q2 and Q3 is inserted; S400: define the evaluations with scores between Q1 and Q3 as available evaluations, extract the features of the available evaluations, determine the modified parts and suggestions, determine the remaining evaluations in the node as extreme evaluations, traverse the user IDs of the extreme evaluations, create a historical evaluation data set, locate the evaluation scale of each user ID, generate a compensation coefficient, and use the compensation coefficient to correct the scores of the extreme evaluations, rearrange the scores of the extreme evaluations, repeat S200 and S300, and update the features; S500: Determine the version of the logo clone, establish a correspondence between a node and the version, link all nodes, generate a linked list, and output the modified part and the suggestion, wherein the linked list is used to represent the version change of the logo clone; S600: integrating a side chain into the linked list, setting a point parallel to the node, and building a coordinated link between the point and the node, wherein the side chain is used to represent several versions of the logo clone; The method further comprises: Locate the tail and the head of the linked list, in the tail, mark the root node for coordinating all nodes and points, in the head, mark the output node, and the output node is integrated with a storage mechanism; The empty points in the side chain are deleted, and the versions of the logo clones in the linked list and the side chain are stored using the storage mechanism.

2. The logo clone online testing method according to claim 1, characterized in that: The S100 includes: Determine the number of logo clone versions that need to be tested. If the number is "1", directly assign the logo clone to the node; If the number is greater than "1", trace back to the source of the logo clone, and determine the primary version and secondary version based on the creative intent of the source; The major version and the minor version are uploaded to a pre-selected test platform.

3. The logo clone online testing method according to claim 2, characterized in that: The S100 further includes: Collecting the evaluations in the test platform, importing the evaluations of the primary version into the nodes, transferring the evaluations of the secondary version into the points, and linking the nodes and points using the overall link; Locate the user ID that posted the review, unify the format of the review, and divide it into words, query the sentiment dictionary, determine the score of each word, and add them up to get the score of the review; Sentence patterns in the evaluation are extracted, and the score is adjusted using the score of the sentence pattern.

4. The logo clone online testing method according to claim 3, characterized in that: The S200 includes: Building a data processing channel between the node and the test platform, and generating a data stream when a new evaluation is generated; Arrange the scores in ascending order and determine Q1, Q2 and Q3, and dynamically update them using the data stream via the data processing channel; The difference between Q3 and Q1 is defined as the interquartile range, and outliers in the arrangement results are deleted if the score of the outlier is greater than or less than .

5. The logo clone online testing method according to claim 3, characterized in that: The S400 includes: Splitting the evaluation into usable evaluation and extreme evaluation, and creating directories for each; Building a mapping relationship between a unique identifier, evaluation, and feature, and transferring the unique identifier and mapping relationship into a node; Extract the modifications and suggestions from the features and sort them by the number of occurrences.

6. The logo clone online testing method according to claim 1, characterized in that: The S500 includes: Determine the version of the logo clone, wherein the version includes at least a first version, a second version, and a third version, and construct nodes having the same number as the version, wherein the nodes include at least a first node, a second node, and a third node; Based on the corresponding relationship, the first version is classified into the first node, and so on; All nodes are integrated to generate a linked list, and a pointer is inserted into the linked list, the pointer being from the first node to the second node.

7. The logo clone online testing method according to claim 2, characterized in that: The S600 includes: Integrate the same number of side chains as the secondary versions into the linked list, synchronize the primary version to the node based on the creation intention, and transfer the secondary version to the point position; Based on the overall link, the evaluation sharing strategy between the linked list and the side chain is determined.

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