CN108171537B - User experience assessment method and device, electronic equipment and storage medium - Google Patents
User experience assessment method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a user experience evaluation method and device, electronic equipment and a storage medium. The method comprises the following steps: the method comprises the steps of obtaining all preset feature words of a target product, sequentially displaying all the feature words according to a preset display rule for each target user, recording reaction data of the target user, and determining and outputting the target feature words according to the reaction data and a preset feature word screening condition. By applying the embodiment of the invention, when the user experience evaluation is carried out, the target characteristic words can be determined based on the preset characteristic word screening conditions, the obtained result is not influenced by the capability of the investigator, the problem of weak reliability of the investigation result caused by using the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
Description
Technical Field
The present invention relates to the field of data analysis and processing technologies, and in particular, to a method and an apparatus for evaluating user experience, an electronic device, and a computer-readable storage medium.
Background
User experience assessment is the study and analysis of a user's experience with respect to various dimensions of a product's functionality, brand, performance, vision, etc. The enterprise can know different feelings of the user for each dimension of the product according to the user experience evaluation result, further adjust a business mode, a service mode, a strategy key point, a profit mode and the like in a targeted mode, and provide a better product or service for the user. Existing user experience assessments are typically conducted in interviews, focus groups, or free associations, etc. The investigator interacts with the investigated user, statistically analyzes the experience of the investigated user on the product, and obtains the user experience evaluation result of the product. The existing method can also obtain the user experience evaluation result of the product by the user according to the result of the questionnaire in a questionnaire mode.
However, the inventor finds that the prior art has at least the following problems in the process of implementing the invention:
when the communication interaction mode is adopted, the investigator needs to adjust the communication mode of the investigator in due time according to the reaction of the investigated user, namely, the interaction capability of the investigator can influence the evaluation result, and the result cannot be quantized. However, when the questionnaire is used, the questionnaire is often personally subjective, and the accuracy and reliability of the result obtained by the investigator based on the questionnaire are low. It can be seen from the above that the accuracy of the user experience evaluation result obtained by the existing method is low.
Disclosure of Invention
The embodiment of the invention aims to provide a user experience evaluation method, a user experience evaluation device, electronic equipment and a computer readable storage medium, so as to improve the accuracy of a user experience evaluation result. The specific technical scheme is as follows:
in a first aspect, to achieve the above object, an embodiment of the present invention discloses a method for evaluating user experience, where the method includes:
acquiring each feature word of a preset target product;
sequentially displaying each feature word according to a preset display rule for each target user, and recording reaction data of the target user, wherein the reaction data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
determining target feature words based on preset feature word screening conditions according to the response data;
and outputting the target characteristic words.
Optionally, the feature words are obtained by inputting the description data of the user for each preset dimension of the target product into a preset feature word generation model.
Optionally, the sequentially displaying each feature word according to a preset display rule includes:
displaying a first characteristic word to be displayed at this time;
when a judgment result of the target user is received, the first characteristic word is cancelled to be displayed;
and when the time length for canceling the display of the first characteristic word reaches a preset first time length, displaying the next characteristic word to be displayed.
Optionally, the feature words include a preset first number of screening feature words, and the number of times of repeatedly displaying the screening feature words is a preset second number;
the determining the target feature words based on preset feature word screening conditions according to the response data comprises the following steps:
determining the second number of judgment results of each screening feature word of each target user, and if the number of continuous and different judgment results in the judgment results corresponding to each screening feature word is not greater than a preset first threshold value, determining the target user as an effective user;
and determining target feature words based on preset feature word screening conditions according to the judgment results of the effective users on the feature words and the judgment duration corresponding to each judgment result.
Optionally, the determining, according to the determination result of the valid user for each feature word and the determination duration corresponding to each determination result, a target feature word based on a preset feature word screening condition includes:
acquiring target response data of the valid user, wherein the target response data comprises valid durations of the valid user for the feature words and a judgment result corresponding to each valid duration, and the valid durations are judgment durations meeting a preset duration range;
and determining target characteristic words based on preset characteristic word screening conditions according to the target response data.
Optionally, the determining, according to the target response data, a target feature word based on a preset feature word screening condition includes:
according to the target response data, judging whether the user proportion occupied by the effective target users of the feature words in the effective users is larger than a preset second threshold value or not aiming at each feature word, wherein the effective target users of the feature words are effective users of which the judgment results of the feature words are preset results;
if the user proportion is larger than the second threshold value, determining the feature word as a core feature word;
for each determined core characteristic word, calculating the average judgment time length of the effective target user of the core characteristic word;
and according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
Optionally, the outputting the target feature word includes:
determining the target dimension with the maximum number of corresponding target feature words in each dimension according to the corresponding relation between the target feature words and each dimension;
and outputting the target feature words and the target dimensions.
In a second aspect, to achieve the above object, an embodiment of the present invention discloses a user experience evaluating apparatus, where the apparatus includes:
the acquisition module is used for acquiring each feature word of a preset target product;
the recording module is used for sequentially displaying each feature word according to a preset display rule for each target user and recording the response data of the target user, wherein the response data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
the determining module is used for determining a target feature word based on a preset feature word screening condition according to the response data;
and the output module is used for outputting the target characteristic words.
Optionally, the feature words are obtained by inputting the description data of the user for each preset dimension of the target product into a preset feature word generation model.
Optionally, the recording module is specifically configured to display a first feature word to be displayed this time;
when a judgment result of the target user is received, the first characteristic word is cancelled to be displayed;
and when the time length for canceling the display of the first characteristic word reaches a preset first time length, displaying the next characteristic word to be displayed.
Optionally, the feature words include a preset first number of screening feature words, and the number of times of repeatedly displaying the screening feature words is a preset second number;
the determining module comprises:
the first determining submodule is used for determining the second number of judgment results of each screening characteristic word of each target user aiming at each target user, and if the number of continuous and different judgment results in the judgment results corresponding to each screening characteristic word is not more than a preset first threshold value, the target user is determined to be an effective user;
and the second determining submodule is used for determining a target feature word based on a preset feature word screening condition according to the judgment result of the effective user on each feature word and the judgment duration corresponding to each judgment result.
Optionally, the second determining sub-module includes:
an obtaining unit, configured to obtain target response data of the valid user, where the target response data includes valid durations of the valid users for the feature words and a determination result corresponding to each of the valid durations, where the valid durations are determination durations that satisfy a preset duration range;
and the determining unit is used for determining the target characteristic words based on preset characteristic word screening conditions according to the target response data.
Optionally, the determining unit is specifically configured to determine, according to the target response data, whether a user proportion occupied by an effective target user of the feature word in the effective users is greater than a preset second threshold for each feature word, where the effective target user of the feature word is an effective user whose determination result on the feature word is a preset result;
if the user proportion is larger than the second threshold value, determining the feature word as a core feature word;
for each determined core characteristic word, calculating the average judgment time length of the effective target user of the core characteristic word;
and according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
Optionally, the output module is specifically configured to determine, according to the corresponding relationship between the target feature words and the dimensions, a target dimension with a largest number of corresponding target feature words in the dimensions;
and outputting the target feature words and the target dimensions.
In order to achieve the above object, an embodiment of the present invention further discloses an electronic device, where the electronic device includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
the memory is used for storing a computer program;
the processor is configured to implement the user experience assessment method according to the first aspect when executing the program stored in the memory.
In a fourth aspect, to achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, where instructions are stored, and when the instructions are executed on a computer, the method for evaluating user experience according to the first aspect is implemented.
In another aspect of the present invention, there is also provided a computer program product including instructions, which when run on a computer, causes the computer to execute the user experience assessment method according to the first aspect.
The embodiment of the invention provides a user experience evaluation method and device, electronic equipment and a computer readable storage medium. According to the method, after the preset feature words of the target product are obtained, each feature word is sequentially displayed according to the preset display rule for each target user, the reaction data of the target user is recorded, and the target feature words are determined and output based on the preset feature word screening conditions. By using the method provided by the embodiment of the invention, the target characteristic words can be determined based on the preset characteristic word screening conditions, the obtained result is not influenced by the capability of the investigator, the problem of poor reliability of the investigation result caused by using the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
Fig. 1 is a flowchart of a user experience assessment method according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for displaying feature words according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for outputting a target feature word according to an embodiment of the present invention;
fig. 4 is a block diagram of a user experience evaluating apparatus according to an embodiment of the present invention;
fig. 5 is a structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention.
In the prior art, investigators often adopt interview and focus group modes to investigate target users. According to the investigation result, the investigator can obtain the user experience evaluation result of the target user for the target product. The investigator can also adopt a questionnaire mode to obtain a user experience evaluation result of the target user for the target product according to the questionnaire filled by the target user. However, the interview and focus group are adopted for investigation, and the accuracy of the investigation result is often influenced by the capability of an investigator; the survey is performed by adopting a questionnaire mode, and the personal subjectivity of the questionnaire also influences the accuracy of the survey result. As can be seen, the accuracy of the survey results of the prior art is low, which in turn results in low accuracy of the user experience assessment results.
Based on the above consideration, the invention provides a user experience assessment method, a user experience assessment device, electronic equipment and a computer-readable storage medium. The method can be applied to a terminal (hereinafter referred to as a terminal) for obtaining a user experience evaluation result, and includes: the terminal can obtain each preset characteristic word of the target product. For each target user, the terminal can sequentially display each feature word according to a preset display rule and record the reaction data of the target user. The terminal can determine and output the target feature words based on preset feature word screening conditions according to the response data. By using the method provided by the embodiment of the invention, the target characteristic words can be determined based on the preset characteristic word screening conditions, the obtained result is not influenced by the capability of the investigator, the problem of poor reliability of the investigation result caused by using the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
The above method is described below with specific examples.
Referring to fig. 1, fig. 1 is a flowchart of a user experience assessment method according to an embodiment of the present invention, including:
s101: and acquiring each characteristic word of a preset target product.
In one implementation, the terminal may store each feature word in advance, or the terminal may generate each feature word before performing the user experience evaluation.
The terminal may generate each feature word by using a preset feature word generation model, and a specific generation process will be described in detail in the following embodiments. The terminal can also acquire each feature word generated manually. Generating each feature word manually may include the following steps: the investigator may first use the 10-point scale to calculate the familiarity of the user with the target product, and then let the user describe the features of the preset dimensions of the target product, where the preset dimensions may include: functionality, performance, content, branding, vision, and interaction. The sentences described by the users are sorted by 2 investigators to generate double words (word format of 2 words), and the ambiguous double words are agreed to ensure that the 2 investigators do not disagree with all the double words. The meaning of all the double words is discussed in the form of a focus group, and the consistent understanding of each double word by all the members of the focus group is ensured to reach more than 85%. One dimension may contain one feature word or may contain a plurality of feature words.
S102: and aiming at each target user, sequentially displaying each characteristic word according to a preset display rule, and recording the reaction data of the target user.
The response data of each target user may include a judgment result of the target user for each feature word and a judgment duration corresponding to the judgment result.
In one implementation, the terminal may first display the product name of the target product before displaying each feature word. The terminal can randomly select one feature word from the undisplayed feature words to display each time, or the terminal can randomly select one feature word from the feature words of a certain dimension to display each time, and after all the feature words of the dimension are displayed, the feature words of the other dimension are displayed until all the feature words of the dimension are displayed.
After seeing a certain feature word, the user can judge whether the feature word can describe the features of the target product, the judgment result is selected through an input component of the terminal, and the terminal can receive the judgment result of the target user on the feature word, wherein the judgment result of the target user on the feature word can be yes or no. For a certain user, the terminal may start timing when displaying the feature word, stop timing when receiving a determination result of the target user for the feature word, and use a time length obtained by timing as the determination time length of the target user for the feature word.
S103: and determining the target characteristic words based on preset characteristic word screening conditions according to the response data.
In one implementation, the terminal may determine the target feature word according to the determination result of the target user, for example, for a certain feature word, if the determination result of more than 80% of the target users for the feature word is "yes", the terminal may determine the feature word as the target feature word. The terminal may also determine the target feature word according to the determination result and the determination duration of the target user, for example, for a certain feature word, if the determination result of more than 70% of the target users for the feature word is yes, and the determination durations of the above 70% of the target users for the feature word are within the preset standard duration range, the terminal may determine the feature word as the target feature word. In general, the target feature words of the target product may be multiple. The method for specifically determining the target feature word will be described in detail in the following embodiments.
S104: and outputting the target characteristic words.
In one implementation, the terminal may send the target feature words to the terminal device used by the investigator after displaying the feature words for all target users is completed.
As can be seen from the above, with the method provided by the embodiment of the present invention, the terminal can determine the target feature word based on the preset feature word screening condition, the obtained result is not affected by the capability of the investigator, the problem of poor reliability of the investigation result caused by using the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
In the embodiment of the invention, the terminal can input the description data of each preset dimension of the target product, which is obtained by the user, into the preset feature word generation model.
In one implementation manner, the terminal may first obtain description data of each preset dimension of the target product from a plurality of users, and then input the description data into a preset feature word generation model to generate feature words of the target product in each dimension. The preset dimensions may include: functionality, performance, content, branding, vision, and interaction. The preset feature Word generation model can be a Word2Vec model, a Doc2Vec model or other text feature extraction models. The model can perform word segmentation on the description data to obtain words with the preset part of speech in the word segmentation result as feature words with the meaning consistent with the meaning expressed by the description data, and can also generate near-meaning words of words with the preset part of speech in the word segmentation result as feature words with the meaning consistent with the meaning expressed by the description data after performing word segmentation on the description data. The preset part of speech may be preset by a technician according to experience, and may be an adjective in a general case. For example, the target product may be a mobile phone, and the terminal may first obtain description data of the user about the dimensions of the mobile phone, such as function, performance, content, brand, vision, and interaction, where the description data may include: the mobile phone has multiple functions, the appearance design of the mobile phone is fashionable, the mobile phone has multiple practical small functions, the mobile phone is very suitable for young people to use, the reaction speed of the mobile phone is high, the color and style of the mobile phone are good, and the cost performance of the mobile phone is high. Correspondingly, the feature words of the mobile phone generated by the terminal may include: multifunctional, fashionable, practical, youth, sensitive, beautiful and high cost performance.
In the embodiment of the invention, the terminal can display two feature words continuously at a certain interval. Referring to fig. 2, fig. 2 is a flowchart of a method for displaying feature words according to an embodiment of the present invention, including:
s201: and displaying the first characteristic word to be displayed at this time.
In one implementation manner, the terminal may randomly select a feature word (i.e., a first feature word) from the feature words and display the feature word, or randomly select a feature word (i.e., a first feature word) from feature words of a certain dimension according to a preset display rule and display the feature word.
S202: and canceling the display of the first characteristic word when the judgment result of the target user is received.
In one implementation manner, the terminal may receive a determination result of the user on the displayed feature word through the input component, and cancel displaying the first feature word when receiving a determination result of the target user on the first feature word.
S203: and when the time length for canceling the display of the first characteristic word reaches the preset first time length, displaying the next characteristic word to be displayed.
In one implementation, the first duration may be preset empirically by a technician. Illustratively, the first duration may be 500 ms. The terminal may count time when the first feature word is canceled from being displayed, and when the counted time length reaches the first time length, one feature word may be selected to be displayed according to the display rule introduced in S102. And the rest can be done until the terminal displays each feature word once.
Therefore, by using the method provided by the embodiment of the invention, the terminal can continuously display two feature words with the first time interval, so as to eliminate the influence of visual aftereffect and improve the accuracy of the judgment result of the target user on each feature word, thereby further improving the accuracy of the user experience evaluation result.
In the embodiment of the invention, the terminal can also use the feature words to screen the target users. Specifically, the feature words may include a preset first number of screening feature words, where the number of times of repeatedly displaying the screening feature words is a preset second number. Determining the target feature word based on the preset feature word screening condition according to the response data (S103), which may include:
and determining a second number of judgment results of each target user for each screened feature word, if the number of continuous and different judgment results in the judgment results corresponding to each screened feature word is not more than a preset first threshold value, determining the target user as an effective user, and then determining the target feature words based on preset feature word screening conditions according to the judgment results of the effective user for each feature word and the judgment duration corresponding to each judgment result.
In one implementation, the terminal may randomly select the selected feature words from the feature words. In addition, the filter feature words may also be set by the investigator. And the terminal can display other characteristic words and/or other screening characteristic words between two times of displaying the same screening characteristic word. For a certain target user, after a certain screening feature word is displayed by the terminal each time, the judgment result of the target user for the screening feature word at this time can be received through the input component, wherein the judgment result of the target user for the screening feature word can be yes or no. For each screened feature word, the terminal may sort the received second number of determination results of the target user for the screened feature word according to the time sequence, and determine whether the number of consecutive differences in the second number of determination results is greater than a first threshold. If the number of the continuous and different judgment results of the target user for each screening feature word is not greater than the first threshold, the terminal can determine the target user as a valid user, otherwise, the terminal can determine the target user as an invalid user.
For example, the 4 determination results of the target user a on the filtered feature words X received by the terminal may be sequentially "yes", and "no", and the 4 determination results of the target user a on the filtered feature words Y may be sequentially "no", "yes", "no", and "yes"; the 4 determination results of the target user B on the filtering feature word X may be sequentially "no", "yes", "no", and the 4 determination results of the target user B on the filtering feature word Y may be sequentially "yes", and "no". The number of the continuous and different judgment results of the target user A on the screening characteristic words X is 1, and the number of the continuous and different judgment results of the target user A on the screening characteristic words Y is 3. The number of the continuous and different judgment results of the target user B on the screening feature words X is 2, and the number of the continuous and different judgment results of the target user B on the screening feature words Y is 1. The terminal may determine that the target user B is a valid user and the target user a is an invalid user. In this embodiment, the second number is only 4, and the first threshold is 2, which are not limited.
The terminal can determine the target characteristic words according to the response data of the effective users.
Therefore, by using the method provided by the embodiment of the invention, the terminal can screen the target user, and the target feature words are determined according to the judgment results of the screened effective users on the feature words and the judgment duration corresponding to each judgment result. Based on the processing, the terminal can remove the reaction data of the target user which is not answered seriously, and further improve the accuracy of the user experience evaluation result.
In the embodiment of the invention, the terminal can further screen the response data of the effective user according to the judgment duration, and determine the target characteristic word according to the screened response data. Specifically, the processing procedure may include:
and acquiring target response data of the effective user, wherein the target response data comprises effective time of the effective user for each feature word and a judgment result corresponding to each effective time, and the effective time is the judgment time meeting a preset time range. And determining the target characteristic words based on preset characteristic word screening conditions according to the target response data.
In one implementation, for each valid user, the lower limit of the preset duration range may be the second duration set by a technician according to experience, and the upper limit of the preset duration range may be the standard deviation of the average judgment duration of the valid user plus the preset first multiple of the judgment duration. The average judgment duration of an effective user can be the average of the judgment durations of the effective user for each feature word, and the standard deviation of the judgment duration of an effective user can be calculated by using a formula (1):
wherein B represents standard deviation of the judging time length, N represents the number of the judging time lengths, mu represents the average value of the judging time lengths, i represents the serial number of the judging time lengths, and X represents the time length of the judging time lengthiIndicating the ith judgment time period. For example, the second time period may be 397ms, and the first multiple may be 3, which is not limited in the present application.
The terminal can determine the target characteristic words according to the target response data of the effective users.
Therefore, by using the method provided by the embodiment of the invention, the terminal can screen the response data of the effective user according to the judgment duration to obtain the target response data, and further determine the target characteristic words. Based on the processing, the reliability of the target response data acquired by the terminal is higher, and the accuracy of the user experience evaluation result is further improved.
In this embodiment of the present invention, the terminal may determine the target feature word according to the target response data, and specifically, the processing step may include:
and judging whether the user proportion of the effective target users of the feature words in the effective users is greater than a preset second threshold value or not according to the target response data and aiming at each feature word, wherein the effective target users of the feature words are effective users of which the judgment result of the feature words is a preset result. And if the user proportion is larger than the second threshold value, determining that the feature word is a core feature word, and if the user proportion is not larger than the second threshold value, not performing any treatment.
In one implementation, the preset result may be "yes". For each feature word, if the determination result of the feature word is that the effective target user is yes, the terminal may determine that the feature word is the core feature word if the proportion of the effective target user in the effective target user is greater than the second threshold. The terminal can determine one core characteristic word or a plurality of core characteristic words. The second threshold may be 75%, which is not limited in this application.
Illustratively, the terminal may determine 10 valid users. For the feature word "youth", if the judgment result of 8 valid users is "yes", the valid target users are 8, and the proportion of the valid target users in the valid users is 8/10-80% > 75%. The terminal can determine the feature word "youth" as the core feature word.
And for each determined core characteristic word, calculating the average judgment time length of the effective target user of the core characteristic word.
In one implementation manner, for each determined core feature word, the terminal may obtain all judgment durations of the effective target user for the core feature word, and calculate an average value of the obtained all judgment durations as an average judgment duration of the core feature word. Illustratively, there are 8 valid target users for the feature word "youth". The terminal can calculate the average value of the judgment duration of the 8 effective target users as the average judgment duration of the core feature word "youth".
And according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
In one implementation, the core feature words determined by the terminal may include "youth", "fashion", "sensitivity", and "multi-function". The average judgment time of the core characteristic word "youth" is 400ms, the average judgment time of the core characteristic word "fashion" is 415ms, the average judgment time of the core characteristic word "sensitive" is 425ms, and the average judgment time of the core characteristic word "multifunctional" is 450 ms. The terminal can determine "youth" and "fashion" as the target feature words. The third number may be 2, which is not limited in this application.
Therefore, by using the method provided by the embodiment of the invention, the terminal can determine the third number of target feature words according to the judgment results and the judgment duration corresponding to the feature words, so that the flexibility and the accuracy of the target feature words are improved.
In the embodiment of the invention, the terminal can also determine the dimensionality of the target product most valued by the target user. Specifically, referring to fig. 3, fig. 3 is a flowchart of a method for outputting a target feature word according to an embodiment of the present invention, where the method includes:
s301: and determining the target dimension with the maximum number of the corresponding target feature words in each dimension according to the corresponding relation between the target feature words and each dimension.
In one implementation, a dimension may include one target feature word or may include a plurality of target feature words. The terminal can obtain the number of the target feature words contained in each dimension according to the dimension to which each target feature word belongs, and determine the dimension containing the most target feature words as the target dimension according to the obtained number.
S302: and outputting the target characteristic words and the target dimensions.
In one implementation, after displaying the feature words for all target users, the terminal may send the target feature words and the determined target dimensions to the terminal device used by the investigator.
Therefore, by the method provided by the embodiment of the invention, the terminal can also output the target dimension, and a more comprehensive user experience evaluation result is provided.
Corresponding to the embodiment of the method shown in fig. 1, referring to fig. 4, fig. 4 is a block diagram of a user experience evaluating apparatus according to an embodiment of the present invention, including:
an obtaining module 401, configured to obtain each feature word of a preset target product;
a recording module 402, configured to sequentially display each feature word according to a preset display rule for each target user, and record response data of the target user, where the response data of each target user includes a determination result of the target user for each feature word and a determination duration corresponding to the determination result;
a determining module 403, configured to determine, according to the response data, a target feature word based on a preset feature word screening condition;
an output module 404, configured to output the target feature word.
In the embodiment of the invention, the feature words are obtained by inputting the description data of the user on the preset dimensions of the target product into a preset feature word generation model.
In the embodiment of the present invention, the recording module 402 is specifically configured to display a first feature word to be displayed this time;
when a judgment result of the target user is received, the first characteristic word is cancelled to be displayed;
and when the time length for canceling the display of the first characteristic word reaches a preset first time length, displaying the next characteristic word to be displayed.
In the embodiment of the invention, the feature words comprise a preset first number of screening feature words, wherein the repeated display times of the screening feature words are a preset second number;
the determining module 403 includes:
the first determining submodule is used for determining the second number of judgment results of each screening characteristic word of each target user aiming at each target user, and if the number of continuous and different judgment results in the judgment results corresponding to each screening characteristic word is not more than a preset first threshold value, the target user is determined to be an effective user;
and the second determining submodule is used for determining a target feature word based on a preset feature word screening condition according to the judgment result of the effective user on each feature word and the judgment duration corresponding to each judgment result.
In an embodiment of the present invention, the second determining sub-module includes:
an obtaining unit, configured to obtain target response data of the valid user, where the target response data includes valid durations of the valid users for the feature words and a determination result corresponding to each of the valid durations, where the valid durations are determination durations that satisfy a preset duration range;
and the determining unit is used for determining the target characteristic words based on preset characteristic word screening conditions according to the target response data.
In an embodiment of the present invention, the determining unit is specifically configured to determine, according to the target response data, whether a user proportion occupied by an effective target user of the feature word in the effective users is greater than a preset second threshold for each feature word, where the effective target user of the feature word is an effective user whose determination result on the feature word is a preset result;
if the user proportion is larger than the second threshold value, determining the feature word as a core feature word;
for each determined core characteristic word, calculating the average judgment time length of the effective target user of the core characteristic word;
and according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
In this embodiment of the present invention, the output module 404 is specifically configured to determine, according to the corresponding relationship between the target feature words and the dimensions, a target dimension with a largest number of corresponding target feature words in the dimensions;
and outputting the target feature words and the target dimensions.
An embodiment of the present invention further provides an electronic device, as shown in fig. 5, which includes a processor 501, a communication interface 502, a memory 503 and a communication bus 504, where the processor 501, the communication interface 502 and the memory 503 complete mutual communication through the communication bus 504,
a memory 503 for storing a computer program;
the processor 501, when executing the program stored in the memory 503, implements the following steps:
acquiring each feature word of a preset target product;
sequentially displaying each feature word according to a preset display rule for each target user, and recording reaction data of the target user, wherein the reaction data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
determining target feature words based on preset feature word screening conditions according to the response data;
and outputting the target characteristic words.
The communication bus 504 mentioned above for the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus 504 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface 502 is used for communication between the above-described electronic apparatus and other apparatuses.
The Memory 503 may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. Optionally, the memory 503 may also be at least one storage device located remotely from the aforementioned processor.
The Processor 501 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the Integrated Circuit may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component.
The electronic equipment provided by the embodiment of the invention can determine the target characteristic words based on the preset characteristic word screening conditions when the user experience evaluation is carried out, the obtained result is not influenced by the abilities of the investigators, the problem of poor reliability of the investigation result caused by the use of the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
In yet another embodiment of the present invention, a computer-readable storage medium is further provided, which has instructions stored therein, which when run on a computer, cause the computer to perform the user experience assessment method described in any of the above embodiments.
Specifically, the user experience assessment method includes:
acquiring each feature word of a preset target product;
sequentially displaying each feature word according to a preset display rule for each target user, and recording reaction data of the target user, wherein the reaction data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
determining target feature words based on preset feature word screening conditions according to the response data;
and outputting the target characteristic words.
It should be noted that other implementation manners of the user experience assessment method are partially the same as those of the foregoing method embodiments, and are not described herein again.
By operating the instructions stored in the computer-readable storage medium provided by the embodiment of the invention, when user experience evaluation is performed, the target feature words can be determined based on the preset feature word screening conditions, the obtained result is not affected by the abilities of the investigators, the problem of poor reliability of the investigation result caused by the use of the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
In yet another embodiment, a computer program product containing instructions is provided, which when run on a computer, causes the computer to perform the user experience assessment method of any of the above embodiments.
Specifically, the user experience assessment method includes:
acquiring each feature word of a preset target product;
sequentially displaying each feature word according to a preset display rule for each target user, and recording reaction data of the target user, wherein the reaction data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
determining target feature words based on preset feature word screening conditions according to the response data;
and outputting the target characteristic words.
It should be noted that other implementation manners of the user experience assessment method are partially the same as those of the foregoing method embodiments, and are not described herein again.
By operating the computer program product provided by the embodiment of the invention, when the user experience evaluation is carried out, the target characteristic words can be determined based on the preset characteristic word screening conditions, the obtained result is not influenced by the abilities of the investigators, the problem of weak reliability of the investigation result caused by the use of the questionnaire can be avoided, and the accuracy of the user experience evaluation result can be improved.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus, the electronic device, the computer-readable storage medium, and the computer program product embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiments.
Claims (14)
1. A method for evaluating user experience, the method comprising:
acquiring each feature word of a preset target product; the feature words are obtained by inputting the description data of the user on the preset dimensions of the target product into a preset feature word generation model;
sequentially displaying each feature word according to a preset display rule for each target user, and recording reaction data of the target user, wherein the reaction data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
determining target feature words based on preset feature word screening conditions according to the response data;
outputting the target characteristic words;
the determining the target feature words based on preset feature word screening conditions according to the response data comprises the following steps:
determining valid users from the target users;
according to the target response data of the effective users, judging whether the user proportion occupied by the effective target users of the feature words in the effective users is larger than a preset second threshold value or not aiming at each feature word, wherein the effective target users of the feature words are effective users of which the judgment results of the feature words are preset results;
if the user proportion is larger than the second threshold value, determining the feature word as a core feature word;
and determining target characteristic words from the core characteristic words based on the determined judgment duration of the effective target users corresponding to the core characteristic words.
2. The method according to claim 1, wherein the sequentially displaying each feature word according to a preset display rule comprises:
displaying a first characteristic word to be displayed at this time;
when a judgment result of the target user is received, the first characteristic word is cancelled to be displayed;
and when the time length for canceling the display of the first characteristic word reaches a preset first time length, displaying the next characteristic word to be displayed.
3. The method according to claim 1, wherein the feature words comprise a preset first number of screening feature words, and the number of times of repeated display of the screening feature words is a preset second number;
the determining the valid users from the target users comprises:
and determining the second number of judgment results of each target user for each screening feature word aiming at each target user, and if the number of continuous and different judgment results in the judgment results corresponding to each screening feature word is not more than a preset first threshold value, determining the target user as an effective user.
4. The method according to claim 3, wherein the target response data includes effective durations of the effective users for the feature words and a judgment result corresponding to each effective duration, wherein the effective durations are judgment durations meeting a preset duration range.
5. The method according to claim 4, wherein the determining target feature words from the core feature words based on the determined judgment duration of the effective target users corresponding to the core feature words comprises:
for each determined core characteristic word, calculating the average judgment time length of the effective target user of the core characteristic word;
and according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
6. The method of claim 1, wherein the outputting the target feature word comprises:
determining the target dimension with the maximum number of corresponding target feature words in each dimension according to the corresponding relation between the target feature words and each dimension;
and outputting the target feature words and the target dimensions.
7. An apparatus for evaluating user experience, the apparatus comprising:
the acquisition module is used for acquiring each feature word of a preset target product; the feature words are obtained by inputting the description data of the user on the preset dimensions of the target product into a preset feature word generation model;
the recording module is used for sequentially displaying each feature word according to a preset display rule for each target user and recording the response data of the target user, wherein the response data of each target user comprises a judgment result of the target user on each feature word and a judgment duration corresponding to the judgment result;
the determining module is used for determining a target feature word based on a preset feature word screening condition according to the response data;
the output module is used for outputting the target characteristic words;
the determining module is specifically configured to determine an effective user from the target users;
according to the target response data of the effective users, judging whether the user proportion occupied by the effective target users of the feature words in the effective users is larger than a preset second threshold value or not aiming at each feature word, wherein the effective target users of the feature words are effective users of which the judgment results of the feature words are preset results;
if the user proportion is larger than the second threshold value, determining the feature word as a core feature word;
and determining target characteristic words from the core characteristic words based on the determined judgment duration of the effective target users corresponding to the core characteristic words.
8. The apparatus of claim 7,
the recording module is specifically used for displaying the first characteristic word to be displayed at this time;
when a judgment result of the target user is received, the first characteristic word is cancelled to be displayed;
and when the time length for canceling the display of the first characteristic word reaches a preset first time length, displaying the next characteristic word to be displayed.
9. The apparatus according to claim 7, wherein the feature words comprise a preset first number of screening feature words, and wherein the number of times of repeated display of the screening feature words is a preset second number;
the determining module comprises:
and the first determining submodule is used for determining the second number of judgment results of each screening characteristic word for each target user, and if the number of continuous and different judgment results in the judgment results corresponding to each screening characteristic word is not more than a preset first threshold value, determining the target user as an effective user.
10. The apparatus according to claim 9, wherein the target response data includes valid durations of the valid users for the feature words and determination results corresponding to each of the valid durations, and wherein the valid durations are determination durations that satisfy a preset duration range.
11. The apparatus of claim 10,
the determining module is specifically configured to calculate, for each determined core feature word, an average judgment duration of an effective target user of the core feature word;
and according to the sequence of the calculated average judging durations from short to long, taking the core feature words corresponding to the previously preset third number of average judging durations as target feature words.
12. The apparatus of claim 7,
the output module is specifically configured to determine, according to the target feature words and the corresponding relationship between the dimensions, a target dimension with the largest number of corresponding target feature words in the dimensions;
and outputting the target feature words and the target dimensions.
13. An electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;
the memory is used for storing a computer program;
the processor, when executing the program stored in the memory, implementing the method steps of any of claims 1-6.
14. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of claims 1 to 6.
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| CN109189465B (en) * | 2018-07-13 | 2022-04-22 | 北京奇艺世纪科技有限公司 | User perception determining method and device and electronic equipment |
| CN110321662A (en) * | 2019-07-18 | 2019-10-11 | 长春工程学院 | A kind of multipurpose Visual Communication Design information processing system and method |
| CN111177337B (en) * | 2019-12-02 | 2023-07-21 | 网之易信息技术（北京）有限公司 | Data processing method and device for questionnaire |
| CN112801690A (en) * | 2020-12-31 | 2021-05-14 | 北京嘀嘀无限科技发展有限公司 | Method and device for determining intervention characteristics |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103582898A (en) * | 2011-05-26 | 2014-02-12 | 创慧株式会社 | Market evaluation investigation device and investigation method |
| CN103886037A (en) * | 2014-03-10 | 2014-06-25 | 华为技术有限公司 | Data screening method and device |
| CN104835087A (en) * | 2015-04-30 | 2015-08-12 | 泸州市金点教育科技有限公司 | Data processing method and apparatus for education test system |
| CN107194743A (en) * | 2017-06-19 | 2017-09-22 | 腾讯科技（深圳）有限公司 | A kind of network surveying questionnaire generation method and device |
| CN107369034A (en) * | 2017-06-14 | 2017-11-21 | 广东数相智能科技有限公司 | A kind of user investigates the sincere method and apparatus judged |
| CN107369041A (en) * | 2017-07-11 | 2017-11-21 | 北京小米移动软件有限公司 | Questionnaire problem determines method and device |
| CN107423356A (en) * | 2017-05-31 | 2017-12-01 | 北京京东尚科信息技术有限公司 | The processing method and processing device of evaluation information, computer-readable medium, electronic equipment |
-
2017
- 2017-12-15 CN CN201711350567.1A patent/CN108171537B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103582898A (en) * | 2011-05-26 | 2014-02-12 | 创慧株式会社 | Market evaluation investigation device and investigation method |
| CN103886037A (en) * | 2014-03-10 | 2014-06-25 | 华为技术有限公司 | Data screening method and device |
| CN104835087A (en) * | 2015-04-30 | 2015-08-12 | 泸州市金点教育科技有限公司 | Data processing method and apparatus for education test system |
| CN107423356A (en) * | 2017-05-31 | 2017-12-01 | 北京京东尚科信息技术有限公司 | The processing method and processing device of evaluation information, computer-readable medium, electronic equipment |
| CN107369034A (en) * | 2017-06-14 | 2017-11-21 | 广东数相智能科技有限公司 | A kind of user investigates the sincere method and apparatus judged |
| CN107194743A (en) * | 2017-06-19 | 2017-09-22 | 腾讯科技（深圳）有限公司 | A kind of network surveying questionnaire generation method and device |
| CN107369041A (en) * | 2017-07-11 | 2017-11-21 | 北京小米移动软件有限公司 | Questionnaire problem determines method and device |
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