CN116821316A - Method and device for acquiring software test asset - Google Patents
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Abstract
The application discloses a method and a device for acquiring a software test asset, and relates to the technical field of big data, wherein the method comprises the following steps: acquiring search content input by a user and position information of the user when the operation of searching the software test asset by the user is monitored; text analysis is carried out on search content input by a user to obtain a plurality of first search keywords; acquiring historical search keywords of a plurality of users in a user group corresponding to position information of the users from a preset corpus; combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results; and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user. The application can accurately determine the search requirement of the user and improve the accuracy of the user in acquiring the software test asset.
Description
Technical Field
The application relates to the technical field of big data, in particular to a method and a device for acquiring software test assets.
Background
This section is intended to provide a background or context to the embodiments of the application that are recited in the claims. The description herein is not admitted to be prior art by inclusion in this section.
In the software testing industry, the software testing assets mainly comprise a testing case library, testing case writing elements, tested system function points, testing rule points, an automatic case library, business trips, testing data construction, testing related technologies, historical production events and the like, and the software testing assets are larger and larger in scale along with the increasing development and perfection of the software testing industry. At present, in the face of huge quantity of software test assets, a user can directly acquire the software test assets corresponding to the search keywords from the plurality of software test assets by inputting the search keywords, however, the search keywords input by the user may not accurately express the search requirements of the user due to the huge quantity and various categories of the software test assets, so that the user cannot obtain accurate search results.
Disclosure of Invention
The embodiment of the application provides a method for acquiring a software test asset, which is used for accurately determining the search requirement of a user and improving the accuracy of acquiring the software test asset by the user, and comprises the following steps:
acquiring search content input by a user and position information of the user when monitoring operation of searching software test assets by the user;
text analysis is carried out on search content input by a user, so that a plurality of first search keywords corresponding to the search content input by the user are obtained;
determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results;
and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user.
The embodiment of the application also provides a device for acquiring the software test asset, which is used for accurately determining the search requirement of the user and improving the accuracy of acquiring the software test asset by the user, and comprises the following steps:
the first acquisition module is used for acquiring search content input by a user and position information of the user when the operation of searching the software test asset by the user is monitored;
the first processing module is used for carrying out text analysis on search content input by a user to obtain a plurality of first search keywords corresponding to the search content input by the user;
the second acquisition module is used for determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
the second processing module is used for analyzing the combination of the historical search keywords of a plurality of users and the first search keywords in the user group corresponding to the position information of the users, and determining a plurality of second search keywords according to analysis results;
and the third acquisition module is used for acquiring the software test assets corresponding to each second search keyword to obtain the software test assets corresponding to the search content input by the user.
The embodiment of the application also provides computer equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method for acquiring the software test asset when executing the computer program.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the method for acquiring the software test asset when being executed by a processor.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is executed by a processor to realize the method for acquiring the software test asset.
In the embodiment of the application, when the operation of searching the software test asset by the user is monitored, the search content input by the user and the position information of the user are acquired; text analysis is carried out on search content input by a user, so that a plurality of first search keywords corresponding to the search content input by the user are obtained; determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users; combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results; and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user. In this way, through analyzing the user input content, firstly determining a plurality of search keywords corresponding to the search content input by the user according to the text analysis of the user input content, then according to the position information of the user, combining the historical search keywords of the user, which are the same as the position information of the user, with the plurality of search keywords corresponding to the search content input by the user to analyze, so as to obtain a final search keyword set, thereby accurately defining the search requirement of the user and improving the accuracy of the user to acquire the software test asset.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art. In the drawings:
FIG. 1 is a flow chart of a method for acquiring a software test asset provided in an embodiment of the application;
FIG. 2 is a flowchart of a method for text analysis of search content entered by a user according to an embodiment of the present application;
FIG. 3 is a flowchart of a method for analyzing a combination of historical search keywords of a plurality of users and a plurality of first search keywords in a user group corresponding to position information of the users according to an embodiment of the present application;
FIG. 4 is a schematic diagram of an apparatus for acquiring a software test asset according to an embodiment of the present application;
fig. 5 is a schematic diagram of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings. The exemplary embodiments of the present application and their descriptions herein are for the purpose of explaining the present application, but are not to be construed as limiting the application.
In the description of the present specification, the terms "comprising," "including," "having," "containing," and the like are open-ended terms, meaning including, but not limited to. The description of the reference terms "one embodiment," "a particular embodiment," "some embodiments," "for example," etc., means that a particular feature, structure, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The order of steps involved in the embodiments is illustrative of the practice of the application, and is not limited and may be suitably modified as desired.
Research shows that with the increasing development and perfection of the software testing industry, the size of the software testing assets is also becoming larger. At present, in the face of huge quantity of software test assets, a user can directly acquire the software test assets corresponding to the search keywords from the plurality of software test assets by inputting the search keywords, however, the search keywords input by the user may not accurately express the search requirements of the user due to the huge quantity and various categories of the software test assets, so that the user cannot obtain accurate search results.
Aiming at the research, the embodiment of the application provides an acquisition scheme of a software test asset, which is used for solving the technical problem that the search keyword input by a user cannot accurately express the search requirement of the user.
As shown in fig. 1, a flowchart of a method for acquiring a software test asset according to an embodiment of the present application may include the following steps:
step 101, acquiring search content input by a user and position information of the user when monitoring operation of searching software test assets by the user;
102, performing text analysis on search content input by a user to obtain a plurality of first search keywords corresponding to the search content input by the user;
step 103, determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
104, combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results;
and 105, acquiring the software test assets corresponding to each second search keyword, and obtaining the software test assets corresponding to the search content input by the user.
In the embodiment of the application, when the operation of searching the software test asset by the user is monitored, the search content input by the user and the position information of the user are acquired; text analysis is carried out on search content input by a user, so that a plurality of first search keywords corresponding to the search content input by the user are obtained; determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users; combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results; and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user. In this way, through analyzing the user input content, firstly determining a plurality of search keywords corresponding to the search content input by the user according to the text analysis of the user input content, then according to the position information of the user, combining the historical search keywords of the user, which are the same as the position information of the user, with the plurality of search keywords corresponding to the search content input by the user to analyze, so as to obtain a final search keyword set, thereby accurately defining the search requirement of the user and improving the accuracy of the user to acquire the software test asset.
The method for acquiring the software test asset will be described in detail.
In the step 101, when the system monitors the operation of searching the software test asset by the user, the search content input by the user and the position information of the user are acquired.
The input format (text format) of the search content input by the user can be pure letters, pure Chinese characters, letter Chinese character combinations, pure numbers, numeral Chinese character combinations, numeral Chinese character letter combinations and the like. For example: the search content entered by the user may be jijin, fund, ji gold, fund 1240, and the like.
The job information of the user may include a department to which the user belongs and a group in which the user is located. For example: the department to which the user belongs is a financial product department, and the group of the user in the department can be a fund group.
In the step 102, text analysis is required for the search content input by the user to obtain a plurality of first search keywords corresponding to the search content input by the user.
In the embodiment of the present application, as shown in fig. 2, text analysis may be performed on search content input by a user by the following method:
step 201, performing error analysis on search content input by a user, and converting the search content input by the user into correct search content when the search content input by the user is wrong; the error analysis includes: one or any combination of mispronounced word analysis, spelling error analysis and pinyin error analysis;
step 202, converting the correct search content according to the text format of the correct search content to obtain a plurality of third search keywords;
in step 203, the text deviation degree of each third search keyword and the search content input by the user is calculated, and the third search keyword corresponding to the text deviation degree smaller than the preset threshold value is used as the first search keyword.
In the implementation, in step 201, since the user may have a problem of input error when inputting the search content, for example, the search content input by the user contains mispronounced words, or may have pinyin error, spelling error, or the like when the search content input by the user is a pure letter, error analysis is required for the search content input by the user, and if the search content input by the user has an error, the search content input by the user is converted into correct search content.
For example, the user enters "i.e., gold" or "progressive", and the correct search content is "fund". For another example, the user inputs "jijin", and the correct search content is "jijin".
In the specific implementation, in step 202, the correct search content is converted according to the text format of the correct search content, so as to obtain a plurality of third search keywords.
For example, if the text format of the correct search content is a pure letter format, the correct search content may be converted into a format of lower case pinyin, upper case pinyin, chinese characters, etc., to obtain a plurality of third search keywords. For example, if the correct search content is "jijin", the third search keyword may be: JIJIN, jijijn, foundation, and the like.
For another example, if the text format of the correct search content is pure Chinese, the text format of the correct search content may be converted into a format such as lower case pinyin, upper case pinyin, etc., to obtain a plurality of third search keywords. For example, if the correct search content is "fund", then the third search key may be: JIJIN, jijijn, foundation, and the like.
In the embodiment of the present application, the search content input by the user may have a hidden meaning, for example, the user inputs a spoken abbreviation of a certain transaction, a non-literal meaning content such as a transaction code, etc., so before the step 202, the hidden meaning analysis may be further performed on the correct search content as follows:
carrying out hidden meaning analysis on the correct search content to determine the hidden meaning of the correct search content;
step 202 may specifically include:
and converting the hidden meaning of the correct search content according to the text format of the hidden meaning of the correct search content to obtain a plurality of third search keywords.
For example: the search content input by the user is '1240' (when no input error exists), and the hidden meaning analysis is performed on the search content input by the user, so that the transaction code that '1240' is 'fund' can be obtained, and therefore 'fund' is the hidden meaning of '1240'. The format of the search content "fund" may be according to: the pure Chinese character format obtains a plurality of search keyword types as follows: foundation, jijin, and the like.
In the specific implementation, in step 203, the text deviation degree of each third search keyword from the search content input by the user may be selected according to the difference degree between the search content input by the user and the third search keyword, and the calculation formula of the difference degree (text deviation degree) may be defined as follows: comparing the difference degree of each obtained third search keyword with a preset threshold value, screening the text deviation degree smaller than the preset threshold value, and taking the corresponding third search keyword as the first search keyword.
For example: if the number of characters of the search content input by the user is x and the number of different characters of any third search keyword and the search content input by the user is k, calculating the difference degree between the search content input by the user and the third search keyword as k/x, and screening out all third search keywords with k/x smaller than m to obtain the first search keyword on the assumption that the set threshold value is m. For example, the user inputs "jijin", and it is necessary to calculate the degree of text deviation of the foundation, jijin, and "jijin", respectively.
In step 103, a user group corresponding to the position information of the user may be determined according to the position information of the user; and then, acquiring historical search keywords of a plurality of users in the user group from a preset corpus.
Wherein, the corpus stores historical search keywords of a plurality of users.
In the embodiment of the application, the position information of the user can comprise the department to which the user belongs and the group of the user in the department;
the determining the user group corresponding to the position information of the user specifically may include:
determining a user group corresponding to a department to which the user belongs and determining a user group corresponding to the group of the user in the department;
the obtaining historical search keywords of a plurality of users in the user group corresponding to the position information of the users from a preset corpus specifically may include:
according to departments to which the users belong, historical search keywords of a plurality of users in a user group corresponding to the departments to which the users belong are obtained from a preset corpus as first historical search keywords, and the first historical search keywords are added into a first historical search keyword set;
according to the group of the user in the department, acquiring historical search keywords of a plurality of users in a user group corresponding to the group of the user in the department from the first historical search keyword set as second historical search keywords, and adding the second historical search keywords into the second historical search keyword set.
In the implementation, for example, historical search keywords of all users in a financial department (a department to which the users belong) can be screened out from a corpus to obtain a first historical search keyword set; and then, screening historical search keywords of all users of a fund group (the group of the users in the department) from a first historical search keyword set of the financial department to obtain a second historical search keyword set.
In the step 104, the historical search keywords of the plurality of users in the user group corresponding to the position information of the screened users may be combined with the plurality of first search keywords obtained in the step 102 to analyze, and a plurality of second search keywords may be determined according to the analysis result.
In an embodiment of the present application, as shown in fig. 3, the step 104 may specifically include:
step 301, matching each first historical search keyword in the first historical search keyword set with each second historical search keyword in the second historical search keyword set, and taking the first historical search keyword as a first vector when the second historical search keyword is contained in the first historical search keyword;
step 302, matching each second historical search keyword in the second historical search keyword set with each first search keyword, and taking the second historical search keywords as second vectors when the first search keywords are contained in the second historical search keywords;
step 303, calculating cosine similarity between each first vector and each second vector;
step 304, ordering the cosine similarity according to the order from small to large; and taking the first historical search keywords of the first vectors and the second historical search keywords of the second vectors, which are corresponding to cosine similarity of a preset proportion and are ranked at the front, as the second search keywords.
In the specific implementation, the method can be respectively fromScreening out first historical search keywords comprising each second historical search keyword in the second historical search keyword set from the first historical search keyword set, and taking the screened first historical search keywords as a first vector f 1 The method comprises the steps of carrying out a first treatment on the surface of the Screening out the second historical search keywords comprising each first search keyword obtained in the step 102 from the second historical search keyword set, and taking the screened out second historical search keywords as a second vector f 2 The method comprises the steps of carrying out a first treatment on the surface of the Then, each f is calculated separately 1 And each f 2 The cosine similarity theta between the two can be calculated by the following formula:
ordering theta from small to large, selecting f corresponding to theta of a preset proportion (such as the first 30%) of the ordered theta 1 First historical search keyword sum f 2 As the second search key.
In step 105, the software test asset is obtained according to the obtained plurality of second search keywords, that is, the software test asset corresponding to the search content input by the user.
By the method for acquiring the software test asset, the historical search records of the user group to which the position information of the user belongs and the search contents input by the user are analyzed, and the search conditions which are most suitable for the search requirements of the user are recommended to the user, so that the technical problem that the search keywords input by the user cannot accurately express the search requirements of the user is solved.
The embodiment of the application also provides a device for acquiring the software test asset, which is described in the following embodiment. Because the principle of the device for solving the problem is similar to that of the method for acquiring the software test asset, the implementation of the device can refer to the implementation of the method for acquiring the software test asset, and the repetition is omitted.
As shown in fig. 4, a schematic diagram of an apparatus for acquiring a software test asset according to an embodiment of the present application may include:
a first obtaining module 401, configured to obtain search content input by a user and job information of the user when operation of searching for a software test asset by the user is monitored;
a first processing module 402, configured to perform text analysis on search content input by a user, to obtain a plurality of first search keywords corresponding to the search content input by the user;
a second obtaining module 403, configured to determine a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
a second processing module 404, configured to analyze a combination of historical search keywords of a plurality of users and a plurality of first search keywords in a user group corresponding to the job information of the user, and determine a plurality of second search keywords according to an analysis result;
and a third obtaining module 405, configured to obtain software test assets corresponding to the search content input by the user, where the software test assets correspond to each second search keyword.
In the embodiment of the present application, the first processing module may be specifically configured to:
performing error analysis on search content input by a user, and converting the search content input by the user into correct search content under the condition that the search content input by the user is wrong; the error analysis includes: one or any combination of mispronounced word analysis, spelling error analysis and pinyin error analysis;
converting the correct search content according to the text format of the correct search content to obtain a plurality of third search keywords;
and calculating the text deviation degree of each third search keyword and the search content input by the user, and taking the third search keyword corresponding to the text deviation degree smaller than the preset threshold value as the first search keyword.
In the embodiment of the present application, a hidden meaning analysis module may be further included, where the hidden meaning analysis module is configured to convert, according to a text format of the correct search content, the correct search content before obtaining the plurality of third search keywords:
carrying out hidden meaning analysis on the correct search content to determine the hidden meaning of the correct search content;
the first processing module may be further configured to:
and converting the hidden meaning of the correct search content according to the text format of the hidden meaning of the correct search content to obtain a plurality of third search keywords.
In the embodiment of the application, the position information of the user can comprise a department to which the user belongs and a group of the user in the department;
a second acquisition module, which may be configured to:
determining a user group corresponding to a department to which the user belongs and determining a user group corresponding to the group of the user in the department;
the second acquisition module is further used for:
according to departments to which the users belong, taking historical search keywords of a plurality of users in a user group corresponding to the departments to which the users belong, which are obtained from a preset corpus, as first historical search keywords, and adding the first historical search keywords into a first historical search keyword set;
according to the group of the users in the department, taking the historical search keywords of a plurality of users in the user group corresponding to the group of the department, which are obtained from the first historical search keyword set, as second historical search keywords, and adding the second historical search keywords into the second historical search keyword set.
In the embodiment of the present application, the second processing module may be specifically configured to:
matching each first historical search keyword in the first historical search keyword set with each second historical search keyword in the second historical search keyword set, and taking the first historical search keywords as first vectors when the second historical search keywords are contained in the first historical search keywords;
matching each second historical search keyword with each first search keyword in the second historical search keyword set, and taking the second historical search keywords as second vectors when the first search keywords are contained in the second historical search keywords;
calculating cosine similarity between each first vector and each second vector;
ordering the cosine similarity according to the order from small to large; and taking the first historical search keywords of the first vectors and the second historical search keywords of the second vectors, which are corresponding to cosine similarity of a preset proportion and are ranked at the front, as the second search keywords.
The embodiment of the present application further provides a computer device, as shown in fig. 5, which is a schematic diagram of the computer device in the embodiment of the present application, where the computer device 500 includes a memory 510, a processor 520, and a computer program 530 stored in the memory 510 and capable of running on the processor 520, and the process 520 implements the method for acquiring the software test asset when executing the computer program 530.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the method for acquiring the software test asset when being executed by a processor.
The embodiment of the application also provides a computer program product, which comprises a computer program, wherein the computer program is executed by a processor to realize the method for acquiring the software test asset.
In the embodiment of the application, when the operation of searching the software test asset by the user is monitored, the search content input by the user and the position information of the user are acquired; text analysis is carried out on search content input by a user, so that a plurality of first search keywords corresponding to the search content input by the user are obtained; determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users; combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results; and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user. In this way, through analyzing the user input content, firstly determining a plurality of search keywords corresponding to the search content input by the user according to the text analysis of the user input content, then according to the position information of the user, combining the historical search keywords of the user, which are the same as the position information of the user, with the plurality of search keywords corresponding to the search content input by the user to analyze, so as to obtain a final search keyword set, thereby accurately defining the search requirement of the user and improving the accuracy of the user to acquire the software test asset.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the application, and is not meant to limit the scope of the application, but to limit the application to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the application are intended to be included within the scope of the application.
Claims (13)
1. A method for acquiring a software test asset, comprising:
acquiring search content input by a user and position information of the user when monitoring operation of searching software test assets by the user;
text analysis is carried out on search content input by a user, so that a plurality of first search keywords corresponding to the search content input by the user are obtained;
determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
combining and analyzing historical search keywords of a plurality of users in a user group corresponding to the position information of the users with a plurality of first search keywords, and determining a plurality of second search keywords according to analysis results;
and acquiring the software test assets corresponding to each second search keyword, and acquiring the software test assets corresponding to the search content input by the user.
2. The method of claim 1, wherein performing text analysis on the search content input by the user to obtain a plurality of first search keywords corresponding to the search content input by the user, comprises:
performing error analysis on search content input by a user, and converting the search content input by the user into correct search content under the condition that the search content input by the user is wrong; the error analysis includes: one or any combination of mispronounced word analysis, spelling error analysis and pinyin error analysis;
converting the correct search content according to the text format of the correct search content to obtain a plurality of third search keywords;
and calculating the text deviation degree of each third search keyword and the search content input by the user, and taking the third search keyword corresponding to the text deviation degree smaller than the preset threshold value as the first search keyword.
3. The method of claim 2, wherein converting the correct search content according to the text format of the correct search content, before obtaining the plurality of third search keywords, further comprises:
carrying out hidden meaning analysis on the correct search content to determine the hidden meaning of the correct search content;
converting the correct search content according to the text format of the correct search content to obtain a plurality of third search keywords, wherein the method comprises the following steps:
and converting the hidden meaning of the correct search content according to the text format of the hidden meaning of the correct search content to obtain a plurality of third search keywords.
4. The method of claim 1, wherein the user's job information includes a department to which the user belongs and a group in which the user is in the department;
determining a user group corresponding to the position information of the user, including:
determining a user group corresponding to a department to which the user belongs and determining a user group corresponding to the group of the user in the department;
acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus, wherein the historical search keywords comprise:
according to departments to which the users belong, taking historical search keywords of a plurality of users in a user group corresponding to the departments to which the users belong, which are obtained from a preset corpus, as first historical search keywords, and adding the first historical search keywords into a first historical search keyword set;
according to the group of the users in the department, taking the historical search keywords of a plurality of users in the user group corresponding to the group of the department, which are obtained from the first historical search keyword set, as second historical search keywords, and adding the second historical search keywords into the second historical search keyword set.
5. The method of claim 4, wherein analyzing the historical search keywords of the plurality of users and the plurality of first search keywords in the user group corresponding to the position information of the users, and determining the plurality of second search keywords according to the analysis result comprises:
matching each first historical search keyword in the first historical search keyword set with each second historical search keyword in the second historical search keyword set, and taking the first historical search keywords as first vectors when the second historical search keywords are contained in the first historical search keywords;
matching each second historical search keyword with each first search keyword in the second historical search keyword set, and taking the second historical search keywords as second vectors when the first search keywords are contained in the second historical search keywords;
calculating cosine similarity between each first vector and each second vector;
ordering the cosine similarity according to the order from small to large; and taking the first historical search keywords of the first vectors and the second historical search keywords of the second vectors, which are corresponding to cosine similarity of a preset proportion and are ranked at the front, as the second search keywords.
6. An apparatus for acquiring a software test asset, comprising:
the first acquisition module is used for acquiring search content input by a user and position information of the user when the operation of searching the software test asset by the user is monitored;
the first processing module is used for carrying out text analysis on search content input by a user to obtain a plurality of first search keywords corresponding to the search content input by the user;
the second acquisition module is used for determining a user group corresponding to the position information of the user; acquiring historical search keywords of a plurality of users in a user group corresponding to the position information of the users from a preset corpus; the corpus stores historical search keywords of a plurality of users;
the second processing module is used for analyzing the combination of the historical search keywords of a plurality of users and the first search keywords in the user group corresponding to the position information of the users, and determining a plurality of second search keywords according to analysis results;
and the third acquisition module is used for acquiring the software test assets corresponding to each second search keyword to obtain the software test assets corresponding to the search content input by the user.
7. The apparatus of claim 6, wherein the first processing module is configured to:
performing error analysis on search content input by a user, and converting the search content input by the user into correct search content under the condition that the search content input by the user is wrong; the error analysis includes: one or any combination of mispronounced word analysis, spelling error analysis and pinyin error analysis;
converting the correct search content according to the text format of the correct search content to obtain a plurality of third search keywords;
and calculating the text deviation degree of each third search keyword and the search content input by the user, and taking the third search keyword corresponding to the text deviation degree smaller than the preset threshold value as the first search keyword.
8. The apparatus of claim 7, further comprising a hidden meaning analysis module for converting the correct search content according to a text format of the correct search content, prior to obtaining the plurality of third search keywords:
carrying out hidden meaning analysis on the correct search content to determine the hidden meaning of the correct search content;
the first processing module is further configured to:
and converting the hidden meaning of the correct search content according to the text format of the hidden meaning of the correct search content to obtain a plurality of third search keywords.
9. The apparatus of claim 6, wherein the user's job information includes a department to which the user belongs and a group in which the user is in the department;
a second acquisition module, configured to:
determining a user group corresponding to a department to which the user belongs and determining a user group corresponding to the group of the user in the department;
the second acquisition module is further used for:
according to departments to which the users belong, taking historical search keywords of a plurality of users in a user group corresponding to the departments to which the users belong, which are obtained from a preset corpus, as first historical search keywords, and adding the first historical search keywords into a first historical search keyword set;
according to the group of the users in the department, taking the historical search keywords of a plurality of users in the user group corresponding to the group of the department, which are obtained from the first historical search keyword set, as second historical search keywords, and adding the second historical search keywords into the second historical search keyword set.
10. The apparatus of claim 9, wherein the second processing module is configured to:
matching each first historical search keyword in the first historical search keyword set with each second historical search keyword in the second historical search keyword set, and taking the first historical search keywords as first vectors when the second historical search keywords are contained in the first historical search keywords;
matching each second historical search keyword with each first search keyword in the second historical search keyword set, and taking the second historical search keywords as second vectors when the first search keywords are contained in the second historical search keywords;
calculating cosine similarity between each first vector and each second vector;
ordering the cosine similarity according to the order from small to large; and taking the first historical search keywords of the first vectors and the second historical search keywords of the second vectors, which are corresponding to cosine similarity of a preset proportion and are ranked at the front, as the second search keywords.
11. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 5 when executing the computer program.
12. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements the method of any of claims 1 to 5.
13. A computer program product, characterized in that the computer program product comprises a computer program which, when executed by a processor, implements the method of any of claims 1 to 5.
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