CN111814040A - Maintenance case searching method and device, terminal equipment and storage medium - Google Patents
Maintenance case searching method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The application is applicable to the technical field of computers, and provides a method, a device, terminal equipment and a storage medium for searching a maintenance case, wherein the method comprises the following steps: acquiring a fault description statement; according to the fault description statement, full-text information matching is carried out on each pre-stored maintenance case through a preset full-text search algorithm, and a matching score corresponding to each maintenance case is determined; and determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores. The embodiment of the application can conveniently and accurately search the maintenance case.
Description
Technical Field
The application belongs to the technical field of computers, and particularly relates to a method and a device for searching a maintenance case, terminal equipment and a storage medium.
Background
With the development of the internet era, vehicle maintenance is not limited to an offline mode any more, and a user can obtain a vehicle maintenance case through internet search, so that the online and intelligent vehicle maintenance is realized.
In the existing maintenance case searching method, a user is usually required to accurately summarize a standard keyword according to the current vehicle condition, and the corresponding maintenance case can be searched by inputting the keyword. However, the searching method has the defect that the maintenance case searching is inaccurate because the user cannot accurately input the keywords.
Disclosure of Invention
In view of this, embodiments of the present application provide a method and an apparatus for searching for a maintenance case, a terminal device, and a storage medium, so as to solve the problem in the prior art how to conveniently and accurately search for a maintenance case.
A first aspect of an embodiment of the present application provides a method for searching for a maintenance case, including:
acquiring a fault description statement;
according to the fault description statement, full-text information matching is carried out on each pre-stored maintenance case through a preset full-text search algorithm, and a matching score corresponding to each maintenance case is determined;
and determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores.
Optionally, the performing full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm, and determining a matching score corresponding to each maintenance case includes:
performing word segmentation processing on the fault description sentences to obtain a target number of fault words;
and respectively determining fault word matching scores corresponding to the maintenance cases and the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
Optionally, the determining, for each pre-stored maintenance case, a matching score of the maintenance case for the fault words corresponding to the target number of fault words, and determining a final matching score of each maintenance case according to the matching score of the fault words includes:
for each prestored maintenance case, the following steps are respectively executed:
calculating first fault word matching scores corresponding to the title field of the maintenance case and the target number of fault words respectively, and determining a first score corresponding to the title field of the maintenance case according to the first fault word matching scores;
calculating second fault word matching scores corresponding to the content fields of the maintenance cases and the target number of fault words respectively, and determining second scores corresponding to the content fields of the maintenance cases according to the second fault word matching scores;
calculating third fault word matching scores corresponding to the keyword fields of the maintenance cases and the target number of fault words respectively, and determining third scores corresponding to the keyword fields of the maintenance cases according to the third fault word matching scores;
calculating fourth fault word matching scores corresponding to the fault description fields of the maintenance cases and the target number of fault words respectively, and determining fourth scores corresponding to the fault description fields of the maintenance cases according to the fourth fault word matching scores;
and calculating a matching score corresponding to the maintenance case according to the first score, the second score, the third score and the fourth score.
Optionally, the calculating a matching score corresponding to the maintenance case according to the first score, the second score, the third score, and the fourth score includes:
determining the score with the largest median among the first score, the second score, the third score and the fourth score as the best score, and taking the other three scores as auxiliary scores;
and obtaining a matching score corresponding to the maintenance case according to the optimal score, the auxiliary score and preset tuning parameters.
Optionally, before the obtaining the fault description statement, the method further includes:
and collecting and storing the maintenance cases to obtain the pre-stored maintenance cases.
Optionally, the collecting and storing the maintenance cases to obtain the pre-stored maintenance cases includes:
and collecting and storing the maintenance cases from any one or more data sources of preset maintenance case specification documents, target maintenance forum data and web crawler data to obtain the pre-stored maintenance cases.
Optionally, after the collecting and storing the maintenance cases and obtaining the pre-stored maintenance cases, the method further includes:
setting corresponding preset weight for each maintenance case according to the data source corresponding to each pre-stored maintenance case;
correspondingly, the performing full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm to determine a matching score corresponding to each maintenance case includes:
and according to the fault description statement and the preset weight, respectively carrying out full-text information matching on each prestored maintenance case through a preset full-text search algorithm, and determining a matching score corresponding to each maintenance case.
A second aspect of an embodiment of the present application provides a maintenance case search apparatus, including:
an acquisition unit configured to acquire a fault description sentence;
the matching score determining unit is used for respectively carrying out full-text information matching on each pre-stored maintenance case through a preset full-text search algorithm according to the fault description statement and determining a matching score corresponding to each maintenance case;
and the target maintenance case determining unit is used for determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores.
Optionally, the matching score determining unit includes a word segmentation module and a matching score determining module:
the word segmentation module is used for carrying out word segmentation processing on the fault description sentences to obtain a target number of fault words;
and the matching score determining module is used for respectively determining the fault word matching scores of the maintenance cases corresponding to the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
The matching score determining unit 32 includes a word segmentation module and a matching score determining module:
the word segmentation module is used for carrying out word segmentation processing on the fault description sentences to obtain a target number of fault words;
and the matching score determining module is used for respectively determining the fault word matching scores of the maintenance cases corresponding to the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
Optionally, the matching score calculating module is specifically configured to determine that one score with the largest median among the first score, the second score, the third score and the fourth score is the best score, and the other three scores are used as auxiliary scores; and obtaining a matching score corresponding to the maintenance case according to the optimal score, the auxiliary score and preset tuning parameters.
Optionally, the service case searching apparatus further includes:
and the maintenance case collecting unit is used for collecting and storing the maintenance cases to obtain the prestored maintenance cases.
Optionally, the maintenance case collecting unit is specifically configured to collect and store a maintenance case from any one or more data sources of a preset maintenance case specification document, target maintenance forum data, and web crawler data, so as to obtain a pre-stored maintenance case.
Optionally, the service case searching apparatus further includes:
the preset weight setting unit is used for setting corresponding preset weights for the maintenance cases according to the data sources respectively corresponding to the pre-stored maintenance cases;
correspondingly, the matching score determining unit is specifically configured to perform full-text information matching on each pre-stored maintenance case through a preset full-text search algorithm according to the fault description statement and the preset weight, and determine a matching score corresponding to each maintenance case.
A third aspect of the embodiments of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is executed by the processor, so that the terminal device implements the steps of the maintenance case search method.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, which stores a computer program that, when executed by a processor, causes a terminal device to implement the steps of the maintenance case search method as described.
A fifth aspect of embodiments of the present application provides a computer program product, which, when running on a terminal device, causes the terminal device to perform the steps of the maintenance case search method according to any one of the first aspects.
Compared with the prior art, the embodiment of the application has the advantages that: in the embodiment of the application, the matching score corresponding to each pre-stored maintenance case can be determined through a pre-set full-text search algorithm only according to a general fault description statement, and the final target maintenance case is determined according to the matching score. The maintenance cases can be searched without being limited to the keywords, and the user does not need to refine the keywords, so that the maintenance cases can be searched more conveniently and quickly, the user experience is improved, and the problem of inaccurate search caused by the fact that the user refines the keywords is avoided; in addition, the matching score corresponding to each maintenance case can be accurately calculated according to the fault description statement and the preset full-text searching algorithm, and the accuracy of the target maintenance case determined according to the matching score is high, so that the accuracy of the maintenance case searching method can be improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic view of an application scenario of a maintenance case searching method according to an embodiment of the present application;
fig. 2 is a schematic flow chart illustrating an implementation of a method for searching a maintenance case according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a maintenance case search apparatus according to an embodiment of the present application;
fig. 4 is a schematic diagram of a terminal device provided in an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In addition, in the description of the present application, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
With the development of online and intelligent vehicle maintenance, a mode of searching for maintenance cases online to obtain corresponding maintenance schemes is adopted by more and more users. However, the existing maintenance case searching mode is limited to keyword searching, so that the maintenance case searching result is inaccurate. The embodiment of the application provides a maintenance case searching method, a maintenance case searching device, terminal equipment and a storage medium, matching scores corresponding to all pre-stored maintenance cases can be determined through a preset full-text searching algorithm only according to general fault description sentences, and final target maintenance cases are determined according to the matching scores, so that accurate searching of the maintenance cases is conveniently and quickly achieved.
An application scenario schematic diagram of the maintenance case searching method according to the embodiment of the application is shown in fig. 1, and includes a user 11, a first terminal device 12, and a second terminal device 13, where the first terminal device 12 and the second terminal device 13 establish a communication connection. In the embodiment of the application, the first terminal device 12 acquires a maintenance case search instruction operated by the user 11, collects a fault description statement described by the user 11, and transmits the fault description statement to the second terminal device 13; the second terminal device 13 obtains the fault description statement sent by the first terminal device 12, and performs full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm, determines a matching score corresponding to each maintenance case, then determines a preset number of target maintenance cases from each pre-stored maintenance case according to the matching scores, and returns the preset number of target maintenance cases to the first terminal device 12 for the user 11 to look up. The first terminal device in the embodiment of the application can comprise terminal devices such as a personal computer, a mobile phone, a tablet personal computer and intelligent wearable device; the second terminal device may include a computer, a server, and other terminal devices. Optionally, the first terminal device is generally a personal device of a user, and the second terminal device is generally a terminal device with a stronger computing capability and a larger storage space maintained by a service provider.
The first embodiment is as follows:
fig. 2 is a schematic flowchart illustrating a flowchart of a maintenance case searching method provided in an embodiment of the present application, where an execution subject of the maintenance case searching method is a terminal device, and may specifically be the second terminal device. The maintenance case search method shown in fig. 2 is detailed as follows:
in S201, a fault description statement is acquired.
The fault description sentence in the embodiment of the application is a sentence for describing the fault condition of the current vehicle by the user, and the sentence can be a general spoken sentence. Illustratively, the "Volkswagen Passat headlamp is not on" may be used as the fault description statement. Alternatively, the fault description statement may be obtained by obtaining voice information of the user or obtaining text information input by the user.
In S202, according to the fault description statement, full-text information matching is performed on each pre-stored maintenance case through a preset full-text search algorithm, and a matching score corresponding to each maintenance case is determined.
In the embodiment of the application, each maintenance case for solving various vehicle faults is stored in the terminal device home terminal or other storage devices connected with the terminal device in advance. After the terminal equipment acquires the fault description statement, each maintenance case prestored in the terminal equipment home terminal or other storage equipment is acquired, and full-text information matching is carried out on each maintenance case and the fault description statement one by one through a preset full-text search algorithm, so that a matching score corresponding to each prestored maintenance case is determined. The preset full-text search algorithm in the embodiment of the application supports matching search of full-text information of the fault description statement without limiting the length and content specification of the fault description statement.
Optionally, in this embodiment of the application, the terminal device specifically executes a preset full-text search algorithm by using a full-text search engine ElasticSearch. The elastic search is a search server based on Lucene, provides a full-text search engine with distributed multi-user capability, is based on a RESTful web interface, can be conveniently installed and used, is designed and used in cloud computing, can achieve real-time search, and has the advantages of stability, reliability and quickness.
Optionally, the step S202 includes:
s20201: and performing word segmentation processing on the fault description sentences to obtain a target number of fault words.
S20202: and respectively determining fault word matching scores corresponding to the maintenance cases and the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
In S20201, the fault description statement is processed by a preset word segmentation algorithm to obtain a target number of fault words. Optionally, the preset word segmentation algorithm may be an algorithm in a chinese word segmentation device in the ElasticSearch, and the word segmentation processing is performed on the fault description sentence through the chinese word segmentation device of the ElasticSearch to obtain the target number of fault words. Optionally, preset word segmentation algorithm processing on the fault description statement may be implemented by a word segmentation neural network, where the word segmentation neural network is obtained by training a large amount of sample data of the fault description statement and is used for performing word segmentation processing on the fault description statement.
Illustratively, for the fault description sentence "the public pascal headlamp is not bright", the preset word segmentation algorithm can obtain 8 fault words, i.e., "the public", "the pascal", "the pizza", "the special", "the front", "the lamp", "not", "bright".
In S20202, for each pre-stored maintenance case, the failure word matching score of each maintenance case and the target number of failure words obtained by the word segmentation processing needs to be calculated, and the matching score of the corresponding maintenance case is determined according to the failure word matching score. Specifically, a maintenance case is sequentially obtained as a current maintenance case; respectively calculating matching scores corresponding to the current maintenance case and each fault word to obtain the target number of fault word matching scores; and accumulating the matching scores of the target number of fault words to obtain a value serving as the matching score of the current maintenance case.
Optionally, the matching score calculation formula for each maintenance case is as follows:
wherein D represents the current maintenance case, q represents the fault description statement, qiRepresenting any fault word obtained by performing word segmentation on the fault description statement, n representing the number of fault words obtained by performing word segmentation on the fault description statement q (namely the target number), and IDF (q)i) Indicating a fault word qiCorresponding Inverse Document Frequencies (IDF), tfNorm (D, q)i) Indicating a fault word qiFrequency (Term Frequency) that occurs in the current service case.
In particular, the amount of the solvent to be used,
IDF(qi)＝log(1+(docCount-docFreq+0.5)/(docFreq+0.5))
wherein, docCount is the total number of all maintenance cases matched with the fault description statement (i.e. the total number of maintenance cases matched with any fault word in the fault description statement), and docFreq represents the current fault word qiNumber of matched maintenance cases. The larger the docCount, the smaller the docFreq, the IDF (q)i) The larger the word q represents the current faultiThe greater the value of (i.e. inverse document frequency IDF (q)), the greater the resolutioni) Is due toBarrier word qiOf importance, IDF (q)i) Larger, say qiThe stronger the importance.
In particular, the amount of the solvent to be used,
tfNorm(D,qi)＝(freq*(k1+1))/(freq+k1*(1-b+b*fieldLength/avgFieldLength))
wherein freq represents fault word qiNumber of occurrences in the current maintenance case, fieldLength indicates the number of occurrences with the fault word q in the current maintenance case DiLength of matching document region (e.g., title region in repair case A contains failure word q)iThe document area length fieldLength is equal to the length of the title area of repair case a), avgfeldlength indicates the sum-of-failure word q in all repair casesiThe average length of the matched document regions, k1 and b, are tuning parameters, illustratively, k1 ═ 1.2, and b ═ 0.75. The larger the fieldLength, the smaller the avgFieldLength, the tfNorm (D, q)i) The larger the value of (A), the more the word q is represented for the faultiThe higher the probability of occurrence in the current service case D.
In the embodiment of the application, the fault description sentences can be automatically subjected to word segmentation, and the final matching scores of all the maintenance cases are determined according to the maintenance cases and the fault word matching scores corresponding to the target number of fault words, so that the matching scores corresponding to the fault description sentences and all the maintenance cases can be accurately calculated, and the accuracy of maintenance case searching is improved.
Optionally, the step S20202 includes:
for each prestored maintenance case, the following steps are respectively executed:
a1: calculating first fault word matching scores corresponding to the title field of the maintenance case and the target number of fault words respectively, and determining a first score corresponding to the title field of the maintenance case according to the first fault word matching scores;
a2: calculating second fault word matching scores corresponding to the content fields of the maintenance cases and the target number of fault words respectively, and determining second scores corresponding to the content fields of the maintenance cases according to the second fault word matching scores;
a3: calculating third fault word matching scores corresponding to the keyword fields of the maintenance cases and the target number of fault words respectively, and determining third scores corresponding to the keyword fields of the maintenance cases according to the third fault word matching scores;
a4: calculating fourth fault word matching scores corresponding to the fault description fields of the maintenance cases and the target number of fault words respectively, and determining fourth scores corresponding to the fault description fields of the maintenance cases according to the fourth fault word matching scores;
a5: and calculating a matching score corresponding to the maintenance case according to the first score, the second score, the third score and the fourth score.
Specifically, in step S20202, the processing from step a1 to step a5 is performed on each pre-stored maintenance case sequentially or simultaneously, so as to obtain a matching score corresponding to each maintenance case. In the embodiment of the application, each pre-stored maintenance case comprises a title field, a content field, a keyword field and a fault description field, wherein the title field describes title information of the maintenance case, the content field describes detailed maintenance content of the maintenance case, the keyword field describes main key information of the maintenance case, the fault description field briefly describes faults which can be solved by the maintenance case, and each maintenance case realizes hierarchical and comprehensive maintenance solution description through the fields.
In step a1, calculating first failure word matching scores corresponding to the title field of the current maintenance case and the target number of failure words respectively, to obtain the target number of first failure word matching scores; and summing the matching scores of the first fault words with the target number to obtain a first score corresponding to the title field of the current maintenance case.
Specifically, the title field of the current maintenance case is represented by DtIndicating that the fault word is qiIndicating that the first failing word match Score is Score (D)t,qi) Indicates that, then, Score (D)t,qi)＝IDF(qi)*tfNorm(Dt,qi) WhereinIDF(qi) Indicating a fault word qiCorresponding inverse document frequency index, tfNorm (D)t,qi) Indicating a fault word qiFrequency index that appears in the title field of the current service case. Correspondingly, the first score
Where n represents the total number of fault words, i.e. the target number.
Exemplarily, let 8 fault words of "popular", "handkerchief", "pizza", "special", "front", "light", "not" and "bright" be obtained in step S20201, and q fault words are applied respectively1～q8Represents; the matching scores of the 8 first fault words corresponding to the 8 fault words in the maintenance case A are set as follows:
Score(Dt,q1)＝IDF(q1)*tfNorm(Dt,q1)＝2.9322188*0.9436971＝2.7671263
Score(Dt,q2)＝IDF(q2)*tfNorm(Dt,q2)＝4.0528555*0.9436971＝3.824668
Score(Dt,q3)＝IDF(q3)*tfNorm(Dt,q3)＝3.84274*0.9436971＝3.6263826
Score(Dt,q4)＝IDF(q4)*tfNorm(Dt,q4)＝4.1724668*0.9436971＝3.9375448
Score(Dt,q5)＝0
Score(Dt,q6)＝IDF(q6)*tfNorm(Dt,q6)＝2.3866072*0.9436971＝2.2522342
Score(Dt,q7)＝IDF(q7)*tfNorm(Dt,q7)＝2.3501973*0.9436971＝2.2178743
Score(Dt,q8)＝IDF(q8)*tfNorm(Dt,q8)＝2.528798*0.9436971＝2.3864195
then, the 8 first failure matching scores are summed to obtain a first Score1 corresponding to the title field of the repair case a:
similarly, in steps a2, A3 and a4, a second Score2 corresponding to the content field of the current maintenance case, a third Score3 corresponding to the keyword field of the current maintenance case and a fourth Score4 corresponding to the fault description field of the current maintenance case are determined, respectively.
In a5, a matching score corresponding to the maintenance case is obtained through a preset algorithm according to the first score, the second score, the third score and the fourth score. Optionally, the preset algorithm may be a value obtained by summing the first score, the second score, the third score and the fourth score, and the value is used as a matching score corresponding to the current maintenance case. Or, the preset algorithm may take a maximum value of the first score, the second score, the third score, and the fourth score as a matching score corresponding to the current maintenance case. Alternatively, the preset algorithm may also be: and multiplying the first score, the second score, the third score and the fourth score by preset weights respectively and then summing to obtain a matching score corresponding to the current maintenance case.
In the embodiment of the application, the first score corresponding to the title field of the maintenance case, the second score corresponding to the content field of the maintenance case, the third score corresponding to the keyword field of the maintenance case and the fourth score corresponding to the fault description field of the maintenance case can be respectively calculated for the target number of fault words, so that comprehensive and accurate matching calculation can be respectively performed on each field of the maintenance case, the matching score of the maintenance case calculated according to the four scores is more accurate, and the accuracy of searching the maintenance case can be further improved.
Optionally, the step a5 includes:
determining the score with the largest median among the first score, the second score, the third score and the fourth score as the best score, and taking the other three scores as auxiliary scores;
and obtaining a matching score corresponding to the maintenance case according to the optimal score, the auxiliary score and preset tuning parameters.
In the embodiment of the application, a method combining optimal matching and parameter optimization is specifically adopted to obtain the matching score corresponding to the maintenance case.
Specifically, the Score with the largest value is determined as the best Score _ main from the first Score, the second Score, the third Score, and the fourth Score, and the other three scores are auxiliary scores. And then, obtaining a matching Score corresponding to the maintenance case according to the optimal Score _ main, the auxiliary Score and a preset optimization parameter tie _ breaker, specifically,
Score＝Score_main+(Score_minor1+Score_minor2+Score_minor3)*tie_breaker
wherein Score _ minor1, Score _ minor2, Score _ minor3 represent three auxiliary scores other than the best Score, respectively.
For example, if the first Score1 corresponding to the title field of the maintenance case a obtained in the step a1 is 21.012249, the second Score2 corresponding to the content field of the maintenance case a obtained in the step a2 is 6.78207, the third Score3 corresponding to the keyword field of the maintenance case a obtained in the step a3 is 3.1499226, and the fourth Score4 corresponding to the fault description field of the maintenance case a obtained in the step A4 is 9.029468, the Score1 is determined as the optimal Score 63main because the value of the Score1 is the largest, and the Score2, Score3 and Score4 are three auxiliary scores (i.e., Score _ Score1 is 63 2, Score _ minor2 is Score3, Score _ minor3 is 4). If the preset tuning parameter tie _ breaker is set to 0.3, the matching score corresponding to the maintenance case a is finally determined as follows:
Score＝Score_main+(Score_minor1+Score_minor2+Score_minor3)*tie_breaker
＝21.012249+(6.78207+3.1499226+9.029468)*0.3
＝26.700687
in the embodiment of the application, the final matching score is obtained by determining the optimal score and the auxiliary score and combining the preset tuning parameters. The matching score corresponding to the maintenance case can be obtained by combining the optimal matching and parameter optimization methods, so that the optimal score can be considered preferentially, and other auxiliary scores can be considered comprehensively to finally obtain the matching score, therefore, the intelligence and the accuracy of the calculation of the matching score can be improved, and the accuracy of the search of the maintenance case is improved.
In S103, a preset number of target maintenance cases are determined from the pre-stored maintenance cases according to the matching scores.
And sequencing all the pre-stored maintenance cases from large to small according to the matching scores, and taking the maintenance cases with the preset number in the front as final target maintenance cases. Optionally, after a preset number of target maintenance cases are determined, the preset number of target maintenance cases are transmitted to a designated user terminal, and the user terminal is instructed to obtain a corresponding maintenance solution conveniently and timely in a text display or voice broadcast mode.
Optionally, before the step S201, the method further includes:
and collecting and storing the maintenance cases to obtain the pre-stored maintenance cases.
In the embodiment of the application, before the fault description statement is obtained, the maintenance case is collected in advance and stored to obtain the pre-stored maintenance case, so that a sufficient maintenance case library is provided for subsequent maintenance case search.
Optionally, the collecting and storing the maintenance cases to obtain the pre-stored maintenance cases includes:
and collecting and storing the maintenance cases from any one or more data sources of preset maintenance case specification documents, target maintenance forum data and web crawler data to obtain the pre-stored maintenance cases.
In the embodiment of the application, the preset maintenance case specification document is a standard maintenance case document provided by a maintenance service provider, and the preset maintenance case specification document is compiled by a professional engineer and has higher reliability after being audited. Illustratively, the preset repair case specification documents are stored in an Object Storage server, for example, in an Object Storage Service (OSS), and each repair case specification document corresponds to a Uniform Resource Locator (URL) in the Object Storage server. Specifically, the title of the maintenance case specification document may be obtained from the object storage server as a title field, and the URL of the maintenance case specification document may be obtained as a content field, and stored in the ElasticSearch, so as to obtain the pre-stored maintenance case.
In the embodiment of the application, the target maintenance forum data is data contained in a technical forum provided by a maintenance service provider. In the technical forum, description areas including a title area, a content area, a keyword area, a fault description area and the like are provided for forum users to fill in so as to realize maintenance scheme sharing of the forum users with relevant tests. Specifically, after data is acquired from the technical forum and text processing is performed, valid data corresponding to a title area is used as a title field, valid data in a content area is used as a content field, valid data corresponding to a keyword area is used as a keyword field, valid data in a fault description area is used as a fault description field and stored in an ElasticSearch, and a pre-stored maintenance case is obtained. Optionally, the text processing includes processing manners such as data cleaning and text merging, where the data cleaning specifically includes operations of determining that data with incomplete information (e.g., posts with only title information) is junk data, removing blank text in the target maintenance forum data, and filtering the blank text, and the text merging includes merging similar texts (e.g., duplicated and pasted repeated texts) in the target maintenance forum data, so as to ensure validity of the extracted data. Alternatively, in the embodiment of the present application, text processing may be implemented by data analysis tools pandas and numpy in the python library.
In the embodiment of the application, the web crawler data are data captured from some websites through the web crawler data. Alternatively, the crawling of the web crawler data may be implemented by a crawling framework script. The Scapy is a quick and high-level screen capture and web capture framework developed by the Python, is used for capturing web sites and extracting structured data from pages, and can improve the convenience, accuracy and efficiency of obtaining the web crawler data due to the strong expansibility and high capture efficiency of the Scapy. Specifically, several common websites with maintenance scheme information can be obtained in advance to serve as the initial domain name of the web crawler, and corresponding web crawler scripts are compiled to capture corresponding web crawler data containing the maintenance scheme information. Specifically, the title data obtained through the web crawler may be used as a title field, the URL of the website page including the maintenance scheme obtained through the web crawler may be used as a content field, and the keyword information, the fault description information, and the like included in the web crawler data may be respectively used as a keyword field and a fault description field and stored in an ElasticSearch to obtain a pre-stored maintenance case.
In the embodiment of the application, the data sources of the maintenance cases specifically comprise various data sources such as preset maintenance case specification documents, target maintenance forum data, web crawler data and the like, the maintenance cases are collected from different data sources and stored, the data volume and content diversity and richness of the prestored maintenance cases can be ensured, the target maintenance cases can be obtained fully and accurately in the follow-up process, and therefore the accuracy of maintenance case searching can be improved.
Optionally, after the collecting and storing the maintenance cases and obtaining the pre-stored maintenance cases, the method further includes:
setting corresponding preset weight for each maintenance case according to the data source corresponding to each pre-stored maintenance case;
correspondingly, the step S202 includes:
and according to the fault description statement and the preset weight, respectively carrying out full-text information matching on each prestored maintenance case through a preset full-text search algorithm, and determining a matching score corresponding to each maintenance case.
In the embodiment of the application, different preset weights are set in the prestored maintenance cases according to the data sources respectively corresponding to the maintenance cases. Specifically, the data source is preset corresponding to the maintenance case of the preset maintenance case specification documentLet the weight be W1The preset weight corresponding to the maintenance case with the data source being the target maintenance forum data is W2The preset weight corresponding to the maintenance case with the data source being web crawler data is W3Since the reliability of the repair case specification document is high, usually W1>W2And W is1>W3Or, further, W1>W2>W3。
Then, correspondingly, in step S202, when calculating the matching score corresponding to each maintenance case, the preset weight is used as a positive correlation factor influencing the matching score (i.e. under the condition that other conditions are not changed, the larger the preset weight of the maintenance case is, the larger the corresponding matching score is). Specifically, after the preliminary matching score corresponding to each maintenance case is preliminarily determined according to a preset full-text search algorithm, the preliminary matching score is multiplied by the preset weight corresponding to the maintenance case to obtain a final matching score.
In the embodiment of the application, different preset weights are set for the maintenance cases of different data sources, so that the score weights of the maintenance cases can be flexibly set according to the reliability of the data sources, and the maintenance cases with larger preset weights can relatively obtain higher matching scores, so that the intelligence and the reliability of the maintenance case search can be improved.
In the embodiment of the application, the matching score corresponding to each pre-stored maintenance case can be determined through a pre-set full-text search algorithm only according to a general fault description statement, and the final target maintenance case is determined according to the matching score. The maintenance cases can be searched without being limited to the keywords, and the user does not need to refine the keywords, so that the maintenance cases can be searched more conveniently and quickly, the user experience is improved, and the problem of inaccurate search caused by the fact that the user refines the keywords is avoided; in addition, the matching score corresponding to each maintenance case can be accurately calculated according to the fault description statement and the preset full-text searching algorithm, and the accuracy of the target maintenance case determined according to the matching score is high, so that the accuracy of the maintenance case searching method can be improved.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Example two:
fig. 3 is a schematic structural diagram of a maintenance case searching apparatus provided in an embodiment of the present application, and for convenience of description, only parts related to the embodiment of the present application are shown:
the maintenance case search device includes: an acquisition unit 31, a matching score determination unit 32, and a target maintenance case determination unit 33. Wherein:
an obtaining unit 31, configured to obtain a fault description statement.
And the matching score determining unit 32 is configured to perform full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm, and determine a matching score corresponding to each maintenance case.
And the target maintenance case determining unit 33 is configured to determine a preset number of target maintenance cases from the pre-stored maintenance cases according to the matching scores.
Optionally, the matching score determining unit 32 includes a word segmentation module and a matching score determining module:
the word segmentation module is used for carrying out word segmentation processing on the fault description sentences to obtain a target number of fault words;
and the matching score determining module is used for respectively determining the fault word matching scores of the maintenance cases corresponding to the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
Optionally, the matching score determining module includes a first score determining module, a second score determining module, a third score determining module, a fourth score determining module, and a matching score calculating module:
the first score determining module is used for calculating first fault word matching scores corresponding to the title fields of the maintenance cases and the target number of fault words respectively, and determining first scores corresponding to the title fields of the maintenance cases according to the first fault word matching scores;
the second score determining module is used for calculating second fault word matching scores corresponding to the content fields of the maintenance cases and the target number of fault words respectively, and determining second scores corresponding to the content fields of the maintenance cases according to the second fault word matching scores;
the third score determining module is used for calculating third fault word matching scores corresponding to the keyword fields of the maintenance cases and the target number of fault words respectively, and determining third scores corresponding to the keyword fields of the maintenance cases according to the third fault word matching scores;
the fourth score determining module is used for calculating fourth fault word matching scores corresponding to the fault description fields of the maintenance cases and the target number of fault words respectively, and determining fourth scores corresponding to the fault description fields of the maintenance cases according to the fourth fault word matching scores;
and the matching score calculating module is used for calculating the matching score corresponding to the maintenance case according to the first score, the second score, the third score and the fourth score.
Optionally, the matching score calculating module is specifically configured to determine that one score with the largest median among the first score, the second score, the third score and the fourth score is the best score, and the other three scores are used as auxiliary scores; and obtaining a matching score corresponding to the maintenance case according to the optimal score, the auxiliary score and preset tuning parameters.
Optionally, the service case searching apparatus further includes:
and the maintenance case collecting unit is used for collecting and storing the maintenance cases to obtain the prestored maintenance cases.
Optionally, the maintenance case collecting unit is specifically configured to collect and store a maintenance case from any one or more data sources of a preset maintenance case specification document, target maintenance forum data, and web crawler data, so as to obtain a pre-stored maintenance case.
Optionally, the service case searching apparatus further includes:
the preset weight setting unit is used for setting corresponding preset weights for the maintenance cases according to the data sources respectively corresponding to the pre-stored maintenance cases;
correspondingly, the matching score determining unit 32 is specifically configured to perform full-text information matching on each pre-stored maintenance case through a preset full-text search algorithm according to the fault description statement and the preset weight, and determine a matching score corresponding to each maintenance case.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Example three:
fig. 4 is a schematic diagram of a terminal device according to an embodiment of the present application. As shown in fig. 4, the terminal device 4 of this embodiment includes: a processor 40, a memory 41, and a computer program 42, such as a service case search program, stored in the memory 41 and operable on the processor 40. The processor 40, when executing the computer program 42, implements the steps in the various service case search method embodiments described above, such as the steps S201 to S203 shown in fig. 2. Alternatively, the processor 40, when executing the computer program 42, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the units 31 to 33 shown in fig. 3.
Illustratively, the computer program 42 may be partitioned into one or more modules/units that are stored in the memory 41 and executed by the processor 40 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 42 in the terminal device 4. For example, the computer program 42 may be divided into an acquisition unit, a matching score determination unit, and a target maintenance case determination unit, and each unit has the following specific functions:
and the acquisition unit is used for acquiring the fault description statement.
And the matching score determining unit is used for respectively carrying out full-text information matching on each pre-stored maintenance case through a preset full-text search algorithm according to the fault description statement and determining the matching score corresponding to each maintenance case.
And the target maintenance case determining unit is used for determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores.
The terminal device 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 40, a memory 41. Those skilled in the art will appreciate that fig. 4 is merely an example of a terminal device 4 and does not constitute a limitation of terminal device 4 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal device may also include input-output devices, network access devices, buses, etc.
The Processor 40 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 41 may be an internal storage unit of the terminal device 4, such as a hard disk or a memory of the terminal device 4. The memory 41 may also be an external storage device of the terminal device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the terminal device 4. The memory 41 is used for storing the computer program and other programs and data required by the terminal device. The memory 41 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (10)
1. A maintenance case search method is characterized by comprising the following steps:
acquiring a fault description statement;
according to the fault description statement, full-text information matching is carried out on each pre-stored maintenance case through a preset full-text search algorithm, and a matching score corresponding to each maintenance case is determined;
and determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores.
2. The method for searching for maintenance cases according to claim 1, wherein the step of performing full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm to determine a matching score corresponding to each maintenance case comprises:
performing word segmentation processing on the fault description sentences to obtain a target number of fault words;
and respectively determining fault word matching scores corresponding to the maintenance cases and the target number of fault words for each pre-stored maintenance case, and determining the final matching score of each maintenance case according to the fault word matching scores.
3. The method as claimed in claim 2, wherein the determining the matching scores of the failure words corresponding to the maintenance cases and the target number of failure words respectively for each pre-stored maintenance case and determining the final matching score of each maintenance case according to the matching scores of the failure words comprises:
for each prestored maintenance case, the following steps are respectively executed:
calculating first fault word matching scores corresponding to the title field of the maintenance case and the target number of fault words respectively, and determining a first score corresponding to the title field of the maintenance case according to the first fault word matching scores;
calculating second fault word matching scores corresponding to the content fields of the maintenance cases and the target number of fault words respectively, and determining second scores corresponding to the content fields of the maintenance cases according to the second fault word matching scores;
calculating third fault word matching scores corresponding to the keyword fields of the maintenance cases and the target number of fault words respectively, and determining third scores corresponding to the keyword fields of the maintenance cases according to the third fault word matching scores;
calculating fourth fault word matching scores corresponding to the fault description fields of the maintenance cases and the target number of fault words respectively, and determining fourth scores corresponding to the fault description fields of the maintenance cases according to the fourth fault word matching scores;
and calculating a matching score corresponding to the maintenance case according to the first score, the second score, the third score and the fourth score.
4. The method of claim 3, wherein the calculating the matching score corresponding to the maintenance case according to the first score, the second score, the third score and the fourth score comprises:
determining the score with the largest median among the first score, the second score, the third score and the fourth score as the best score, and taking the other three scores as auxiliary scores;
and obtaining a matching score corresponding to the maintenance case according to the optimal score, the auxiliary score and preset tuning parameters.
5. The repair case search method according to any one of claims 1 to 4, further comprising, before the obtaining the fault description statement:
and collecting and storing the maintenance cases to obtain the pre-stored maintenance cases.
6. The method as claimed in claim 5, wherein the collecting and storing the maintenance cases to obtain the pre-stored maintenance cases comprises:
and collecting and storing the maintenance cases from any one or more data sources of preset maintenance case specification documents, target maintenance forum data and web crawler data to obtain the pre-stored maintenance cases.
7. The method as claimed in claim 6, wherein after collecting and storing the service cases to obtain the pre-stored service cases, the method further comprises:
setting corresponding preset weight for each maintenance case according to the data source corresponding to each pre-stored maintenance case;
correspondingly, the performing full-text information matching on each pre-stored maintenance case according to the fault description statement by using a preset full-text search algorithm to determine a matching score corresponding to each maintenance case includes:
and according to the fault description statement and the preset weight, respectively carrying out full-text information matching on each prestored maintenance case through a preset full-text search algorithm, and determining a matching score corresponding to each maintenance case.
8. A service case search apparatus, comprising:
an acquisition unit configured to acquire a fault description sentence;
the matching score determining unit is used for respectively carrying out full-text information matching on each pre-stored maintenance case through a preset full-text search algorithm according to the fault description statement and determining a matching score corresponding to each maintenance case;
and the target maintenance case determining unit is used for determining a preset number of target maintenance cases from the prestored maintenance cases according to the matching scores.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the computer program, when executed by the processor, causes the terminal device to carry out the steps of the method according to any one of claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, causes a terminal device to carry out the steps of the method according to any one of claims 1 to 7.
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