Methods, devices, computer equipment, and storage media for tracing demand information

Abstract

This application discloses a method, apparatus, computer device, and storage medium for tracing the source of demand information, comprising: acquiring a pre-set historical demand document library, and acquiring demand summary information and basic document information corresponding to each historical demand document in the historical demand document library; tracing the source of each historical demand document based on the demand summary information and basic document information, and generating iterative relationship information for each historical demand document; when a demand search request is received, acquiring the search permissions and demand search statement corresponding to the demand search request; performing word segmentation on the demand search statement to obtain multiple target words, and acquiring synonyms corresponding to each target word to obtain target search terms; searching for target demand documents corresponding to target search terms according to search permissions, and acquiring a list of historical demand documents that are from the same source as the target demand documents based on the iterative relationship information.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of document management, and in particular to a method, apparatus, computer equipment and storage medium for tracing demand information. Background Technology

[0002] In the daily development process, requirements documents are important standard documents that guide the work of the development team. Product designers usually write the product requirements into documents so that the development team can understand the requirements information.

[0003] As the number of requirement documents managed by an enterprise or platform gradually increases, it often leads to problems of difficulty in tracing back to the source. For example, it is difficult to find out which requirement document a certain function of a certain business system was recorded in, or in which requirement document a certain function was first proposed. It can be seen that there are technical problems of difficulty in tracing back the requirement information. Summary of the Invention

[0004] This invention provides a method, apparatus, computer equipment, and storage medium for tracing demand information, which can improve the efficiency of demand information tracing.

[0005] To solve the above-mentioned technical problems, one technical solution adopted by the embodiments of the present invention is: to provide a method for tracing demand information, including:

[0006] Obtain a pre-set historical requirement document library, and obtain the requirement summary information and basic document information corresponding to each historical requirement document in the historical requirement document library;

[0007] Based on the requirement summary information and the document basic information, the requirement document tracing is performed on each historical requirement document, and the iteration relationship information of each historical requirement document is generated;

[0008] When a demand search request is received, the search permissions and demand search statement corresponding to the demand search request are obtained;

[0009] The search query is segmented to obtain multiple target words, and the synonyms corresponding to each target word are obtained to obtain the target search terms.

[0010] According to the search permissions, find the target requirement document corresponding to the target search term, and according to the iteration relationship information, obtain a list of historical requirement documents that are from the same source as the target requirement document.

[0011] Optionally, obtaining a pre-set historical requirement document library and obtaining the requirement summary information and basic document information corresponding to each historical requirement document in the historical requirement document library includes:

[0012] Receive a historical requirement document update request, and obtain a preset historical requirement document library through the historical requirement document update request, the historical requirement document library including multiple historical requirement documents;

[0013] Read the basic document information corresponding to each historical requirement document, including version information, upload time, uploader information, and development object information;

[0014] Using a pre-built document reading and writing tool, the formatted content of each historical requirement document is read to obtain the requirement summary information corresponding to each historical requirement document. The requirement summary information is used to indicate the title formatted text information in the content of the corresponding historical requirement document.

[0015] Optionally, the step of tracing the origins of each historical requirement document based on the requirement summary information and the document basic information, and generating iterative relationship information for each historical requirement document, includes:

[0016] Based on the aforementioned requirement summary information, document content matching is performed on each historical requirement document to obtain a list of associated requirement documents corresponding to each historical requirement document;

[0017] By using the uploader information and development object information in the basic information of the document, the list of related requirement documents corresponding to each historical requirement document is classified by development main line to obtain the list of source requirement documents corresponding to each historical requirement document.

[0018] Based on the version information and upload time in the basic document information, the list of source requirement documents corresponding to each historical requirement document is iteratively bound to obtain the iterative relationship information of each historical requirement document.

[0019] Optionally, the step of matching the document content of each historical requirement document according to the requirement summary information to obtain a list of associated requirement documents corresponding to each historical requirement document includes:

[0020] The demand summary information is segmented into words to obtain multiple summary words, and the synonyms corresponding to each summary word are obtained to obtain summary search terms;

[0021] Using the summary search terms, the document content of each historical requirement document is traversed to obtain a list of matching requirement documents corresponding to each historical requirement document. The list of matching requirement documents includes historical requirement documents that match at least one summary search term.

[0022] Historical requirement documents with fewer than a preset threshold number of matched summary search terms in the matching requirement document list are removed, resulting in a list of associated requirement documents for each historical requirement document.

[0023] Optionally, when a search request is received, obtaining the search permissions and search statement corresponding to the search request includes:

[0024] When a demand search request is received, extract the requester information and the demand search statement from the demand search request.

[0025] The system retrieves the level information corresponding to the requester's information from the preset organizational structure information and obtains the search permissions corresponding to the level information. The search permissions are used to indicate the document search scope corresponding to the request.

[0026] Optionally, the search query is segmented to obtain multiple target words, and synonyms for each target word are obtained, resulting in target search terms including:

[0027] The search query is segmented using the Jieba word segmentation algorithm to obtain multiple initial word segments. Stop words in the initial word segments are then filtered out to obtain multiple target word segments.

[0028] Each target word segment is vectorized to obtain the embedded word vector corresponding to each target word segment.

[0029] The cosine distance algorithm is used to obtain the synonyms corresponding to each target word segment from the preset embedding lexicon to obtain the target search term. The target search term is used to indicate the embedding word vectors whose cosine distance is less than a preset cosine threshold.

[0030] Optionally, the step of searching for the target requirement document corresponding to the target search term according to the search permissions, and obtaining a list of historical requirement documents that are from the same source as the target requirement document according to the iteration relationship information, includes:

[0031] Within the document search range corresponding to the search permission, the document content of the corresponding historical requirement documents in the historical requirement document library is traversed to obtain the candidate requirement documents corresponding to the target search term. The candidate requirement documents are used to indicate the historical requirement documents containing the target search term.

[0032] The target search term hit rate is calculated for the candidate demand documents to obtain the target demand document with the highest target search term hit rate;

[0033] Based on the iterative relationship information, obtain the list of source requirement documents corresponding to the target requirement document, and set the list of source requirement documents corresponding to the target requirement document as the list of historical requirement documents associated with the target requirement document.

[0034] To address the aforementioned technical problems, embodiments of the present invention also provide a traceability device for demand information, comprising:

[0035] The acquisition module is used to acquire a pre-set historical requirement document library, and to acquire the requirement summary information and document basic information corresponding to each historical requirement document in the historical requirement document library;

[0036] The tracing module is used to trace the origin of each historical requirement document based on the requirement summary information and the document basic information, and to generate iterative relationship information for each historical requirement document.

[0037] The receiving module is used to obtain the search permissions and search statements corresponding to the search request when it receives a search request.

[0038] The word segmentation module is used to segment the search query into multiple target words and obtain the synonyms corresponding to each target word to obtain the target search term.

[0039] The search module is used to search for the target requirement document corresponding to the target search term according to the search permissions, and to obtain a list of historical requirement documents that are from the same source as the target requirement document according to the iteration relationship information.

[0040] Optionally, the acquisition module is specifically used for:

[0041] Receive a historical requirement document update request, and obtain a preset historical requirement document library through the historical requirement document update request, the historical requirement document library including multiple historical requirement documents;

[0042] Read the basic document information corresponding to each historical requirement document, including version information, upload time, uploader information, and development object information;

[0043] Using a pre-built document reading and writing tool, the formatted content of each historical requirement document is read to obtain the requirement summary information corresponding to each historical requirement document. The requirement summary information is used to indicate the title formatted text information in the content of the corresponding historical requirement document.

[0044] Optionally, the traceability module includes:

[0045] The matching unit is used to perform document content matching for each historical requirement document according to the requirement summary information, so as to obtain a list of associated requirement documents corresponding to each historical requirement document;

[0046] The classification unit is used to classify the list of related requirement documents corresponding to each historical requirement document by the development main line through the uploader information and development object information in the basic information of the document, so as to obtain the list of source requirement documents corresponding to each historical requirement document.

[0047] The binding unit is used to perform iterative relationship binding on the list of source requirement documents corresponding to each historical requirement document based on the version information and upload time in the basic document information, so as to obtain the iterative relationship information of each historical requirement document.

[0048] Optionally, the matching unit is specifically used for:

[0049] The demand summary information is segmented into words to obtain multiple summary words, and the synonyms corresponding to each summary word are obtained to obtain summary search terms;

[0050] Using the summary search terms, the document content of each historical requirement document is traversed to obtain a list of matching requirement documents corresponding to each historical requirement document. The list of matching requirement documents includes historical requirement documents that match at least one summary search term.

[0051] Historical requirement documents with fewer than a preset threshold number of matched summary search terms in the matching requirement document list are removed, resulting in a list of associated requirement documents for each historical requirement document.

[0052] Optionally, the receiving module is specifically used for:

[0053] When a demand search request is received, extract the requester information and the demand search statement from the demand search request.

[0054] The system retrieves the level information corresponding to the requester's information from the preset organizational structure information and obtains the search permissions corresponding to the level information. The search permissions are used to indicate the document search scope corresponding to the request.

[0055] Optionally, the word segmentation module is specifically used for:

[0056] The search query is segmented using the Jieba word segmentation algorithm to obtain multiple initial word segments. Stop words in the initial word segments are then filtered out to obtain multiple target word segments.

[0057] Each target word segment is vectorized to obtain the embedded word vector corresponding to each target word segment.

[0058] The cosine distance algorithm is used to obtain the synonyms corresponding to each target word segment from the preset embedding lexicon to obtain the target search term. The target search term is used to indicate the embedding word vectors whose cosine distance is less than a preset cosine threshold.

[0059] Optionally, the search module is specifically used for:

[0060] Within the document search range corresponding to the search permission, the document content of the corresponding historical requirement documents in the historical requirement document library is traversed to obtain the candidate requirement documents corresponding to the target search term. The candidate requirement documents are used to indicate the historical requirement documents containing the target search term.

[0061] The target search term hit rate is calculated for the candidate demand documents to obtain the target demand document with the highest target search term hit rate;

[0062] Based on the iterative relationship information, obtain the list of source requirement documents corresponding to the target requirement document, and set the list of source requirement documents corresponding to the target requirement document as the list of historical requirement documents associated with the target requirement document.

[0063] To address the aforementioned technical problems, this invention also provides a computer device, including a memory and a processor. The memory stores computer-readable instructions, which, when executed by the processor, cause the processor to perform the steps of the aforementioned method for tracing the source of demand information.

[0064] To address the aforementioned technical problems, this embodiment of the invention also provides a computer storage medium, wherein when the computer-readable instructions are executed by one or more processors, the one or more processors perform the steps of the aforementioned method for tracing the source of demand information.

[0065] The beneficial effects of this invention are: by tracing the origins of multiple historical requirement documents in the historical requirement document library, determining the iteration relationship information of each historical requirement document, and when a requirement search request is received, after finding the most similar target requirement document in the historical requirement document library, a list of historical requirement documents that are from the same source as the target requirement document is obtained according to the iteration relationship information, which can improve the efficiency of requirement information tracing. Attached Figure Description

[0066] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0067] Figure 1 A basic flowchart illustrating a method for tracing demand information in a specific embodiment of this application;

[0068] Figure 2 This is a schematic diagram of an embodiment of the method for tracing demand information in this application;

[0069] Figure 3 This is a schematic diagram of another embodiment of the method for tracing demand information in this application;

[0070] Figure 4This is a schematic diagram of the basic structure of a demand information tracing device according to one embodiment of this application;

[0071] Figure 5 This is a basic structural block diagram of a computer device according to an embodiment of this application. Detailed Implementation

[0072] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0073] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the word “comprising” as used in the specification of this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0074] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0075] Those skilled in the art will understand that the term "terminal" as used herein includes both devices that are wireless signal receivers, devices that are wireless signal receivers without transmitting capability, and devices with receiving and transmitting hardware, having receiving and transmitting hardware capable of performing bidirectional communication on a bidirectional communication link. Such devices may include: cellular or other communication devices having a single-line display, a multi-line display, or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDA (Personal Digital Assistant) that may include a radio frequency receiver, pager, Internet / intranet access, web browser, notepad, calendar, and / or GPS (Global Positioning System) receiver; and conventional laptop and / or handheld computers or other devices that have and / or include a radio frequency receiver. As used herein, "terminal" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally, and / or in a distributed manner, operating in any other location on Earth and / or in space. "Terminal" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0076] Please see Figure 1 , Figure 1 This is a schematic diagram illustrating the basic process of the requirement information tracing method in this embodiment. For example... Figure 1 As shown, a method for tracing demand information includes:

[0077] S100. Obtain a pre-set historical requirement document library, and obtain the requirement summary information and document basic information corresponding to each historical requirement document in the historical requirement document library;

[0078] In this embodiment, the pre-set historical requirement document library includes multiple historical requirement documents. Each historical requirement document records development requirement information, which describes specific development requirements, such as the development requirement information for the login function of a sales system.

[0079] In this embodiment, the requirement summary information corresponding to each historical requirement document is used to indicate the summary of the development requirement information. The requirement summary information can be obtained through preset configuration information or by extracting information such as titles and keywords from the corresponding historical requirement documents. No specific limitation is made.

[0080] In this embodiment, the basic information corresponding to each historical requirement document includes version information, upload time, uploader information, development object information, and document title. The development object information indicates the object described in the corresponding historical requirement document. For example, if a historical requirement document describes the requirements for a sales system, then the sales system is the development object. The version information indicates the development version of the development object, the upload time indicates the upload time of the corresponding historical requirement document, the uploader information indicates the uploader information of the corresponding historical requirement document, and the document title indicates the title of the corresponding historical requirement document.

[0081] S200. Based on the requirement summary information and the document basic information, perform requirement document tracing for each historical requirement document and generate iteration relationship information for each historical requirement document;

[0082] In this embodiment, since there may be iterative relationships between different historical requirement documents, and it is difficult to identify the iterative relationships of specific requirements using only development version information, combining requirement summary information and document basic information to trace the source of requirement documents can satisfy the identification of the iterative relationships of specific requirements in each historical requirement document. For example, if the development requirement of a certain function exists in multiple historical requirement documents, the iterative relationship information of the historical requirement documents recording the function and each historical requirement document can be determined by tracing the source of requirement documents.

[0083] In this embodiment, the requirement summary information corresponding to each historical requirement document is searched in the historical requirement document library to obtain the associated requirement document corresponding to the requirement summary information. Then, according to the basic information of the document corresponding to the associated requirement document, the iteration relationship information of each historical requirement document is determined. The iteration relationship information is used to indicate the iteration relationship between historical requirement documents on the same development pipeline.

[0084] S300. When a demand search request is received, obtain the search permissions and demand search statement corresponding to the demand search request.

[0085] In this embodiment, the terminal sends a requirement search request, which includes a requirement search statement and an identity identifier. The search permission corresponding to the requirement search request is obtained through the identity identifier. The search permission is used to indicate the searchable scope corresponding to the identity identifier. For example, the identity identifier of a certain development team member can only be used to indicate the search of historical requirement documents uploaded by that development team.

[0086] Specifically, S300 includes: when a demand search request is received, extracting the requester information and demand search statement from the demand search request; searching for the level information corresponding to the requester information from preset organizational structure information, and obtaining the search permission corresponding to the level information, wherein the search permission is used to indicate the document search scope corresponding to the demand search request.

[0087] In this embodiment, in order to improve the data security of the historical requirements document library and avoid the leakage of development requirements data, the scope of document search for the requester is limited by search permissions. Specifically, when a requirements search request is received from the terminal, the corresponding level information is searched from the preset organizational structure information based on the requester information in the requirements search request. That is, the functional level of the requester information, such as basic level, manager level and decision-maker level, etc., and then the search permissions corresponding to the requester information are determined based on the level information.

[0088] S400. Perform word segmentation on the search query to obtain multiple target words, and obtain the synonyms corresponding to each target word to obtain the target search term;

[0089] In this embodiment, the demand search statement includes several search statements, such as "the login function of system A" and "what is the transmission method used by the data mining interface". The target search terms are generated by the trained search term generation model. The target search terms include the original word, the synonyms and near-synonyms of the original word. The search term generation model vectorizes the demand search statement to obtain a vectorized statement, and then segments the vectorized statement to obtain multiple target words. The model then obtains the synonyms and near-synonyms of each target word from a pre-set thesaurus, thereby obtaining the target search terms.

[0090] Specifically, S400 includes: performing word segmentation on the search query using the Jieba word segmentation algorithm to obtain multiple initial word segments, and filtering out stop words from the initial word segments to obtain multiple target word segments; performing vectorization on each target word segment to obtain the embedded word vector corresponding to each target word segment; and using the cosine distance algorithm to obtain the synonyms corresponding to each target word segment from a preset embedded word library to obtain the target search term, wherein the target search term is used to indicate the embedded word vectors whose cosine distance is less than a preset cosine threshold.

[0091] In this embodiment, in order to improve the acquisition efficiency of the target search term, the requirement search statement is segmented by the Jieba segmentation algorithm to obtain multiple initial segments, and stop words such as "de, le, a" are filtered. Then, each target segment is transformed into an embedded word vector Embedding. The words in Embedding topology can map high-dimensional raw data to a low-dimensional manifold, making the high-dimensional raw data separable after being mapped to the low-dimensional manifold, that is, the embedded word vector. By calculating the distance between vectors through the cosine distance algorithm, the similarity between vectors can be determined. The cosine distance between the embedded word vector corresponding to each target segment and the embedded words in the preset embedded word library is calculated, and the embedded word vector with a cosine distance less than the preset cosine threshold is set as the synonym of the corresponding target segment, so as to obtain the target search term.

[0092] S500. According to the search authority, search for the target requirement document corresponding to the target search term, and obtain a list of historical requirement documents homologous to the target requirement document according to the iterative relationship information.

[0093] In this embodiment, in order to improve the security of historical requirement documents, the target requirement document is searched according to the search authority. The search authority is used to indicate the searchable range in the historical requirement document library, that is, the searchable historical requirement documents. Searching for the target requirement document corresponding to the target search term in the searchable historical requirement documents can improve the data security in the historical requirement document library.

[0094] In this embodiment, the target requirement document is used to indicate the historical requirement document with the highest matching degree to the target search term. The historical requirement documents homologous to the target requirement document are found through the iterative relationship information to obtain a list of homologous historical requirement documents. Among them, the list of homologous historical requirement documents is used to indicate the historical requirement documents with the same source as the target requirement document.

[0095] Specifically, S500 includes: traversing the document content of the corresponding historical requirement documents in the historical requirement document library within the document search range corresponding to the search authority to obtain candidate requirement documents corresponding to the target search term. The candidate requirement documents are used to indicate the historical requirement documents containing the target search term; calculating the hit rate of the target search term for the candidate requirement documents to obtain the target requirement document with the highest hit rate of the target search term; obtaining a list of homologous requirement documents corresponding to the target requirement document according to the iterative relationship information, and setting the list of homologous requirement documents corresponding to the target requirement document as the list of historical requirement documents associated with the target requirement document.

[0096] In this embodiment, document content is traversed within the document search range corresponding to the search permission to obtain candidate demand documents. The historical demand documents in the candidate demand documents are those containing the target search term. This step is a fuzzy search. By calculating the target search term hit rate of the candidate demand documents, the target demand document with the highest target search term hit rate is obtained. Finally, the list of homologous demand documents corresponding to the target demand document is obtained to determine the list of historical demand documents associated with the target demand document.

[0097] Please see Figure 2 One embodiment of the demand information tracing method in this invention includes:

[0098] like Figure 2 As shown, S100 includes:

[0099] S110. Receive a historical requirement document update request, and obtain a preset historical requirement document library through the historical requirement document update request, wherein the historical requirement document library includes multiple historical requirement documents;

[0100] In this embodiment, the historical requirement document update request is used to instruct the updating of the iteration relationship information of each historical requirement document. It can be triggered when the historical requirement document library receives a new requirement document upload, or it can be triggered periodically by a scheduled task; the specific triggering method is not limited. When the historical requirement document library receives a new requirement document upload, the requirement summary information and basic document information of the new requirement document are extracted. The original iteration relationship information of each historical requirement document in the historical requirement document library (excluding the new requirement document) is obtained. Using the requirement summary information and basic document information of the new requirement document, the iteration relationship of the new requirement document in the original iteration relationship information is determined, thereby obtaining the new iteration relationship information (including the new requirement document).

[0101] S120. Read the basic information of each historical requirement document, including version information, upload time, uploader information and development object information.

[0102] In this embodiment, the basic document information corresponding to each historical requirement document includes the version information, upload time, uploader information, and development object information of the corresponding historical requirement document.

[0103] S130. Using a pre-set document reading and writing tool, read the formatted content of each historical requirement document to obtain the requirement summary information corresponding to each historical requirement document. The requirement summary information is used to indicate the title formatted text information in the content of the corresponding historical requirement document.

[0104] In this embodiment, the pre-built document reading and writing tool traverses each line of content in each historical requirement document and reads the format information of each line of content to determine the title format text information corresponding to each historical requirement document, i.e. requirement summary information. In addition, the requirement summary information can also be used to indicate specific format text information in the content of the corresponding requirement document. The specific format can be pre-configured and is not limited in any way.

[0105] Please see Figure 3 Another embodiment of the demand information tracing method in this invention includes:

[0106] like Figure 3 As shown, S200 includes:

[0107] S210. According to the requirement summary information, perform document content matching on each historical requirement document to obtain a list of associated requirement documents corresponding to each historical requirement document.

[0108] In this embodiment, in order to improve the efficiency of requirement document tracing, the document content is matched with each second historical requirement document (excluding the first historical requirement document) in the historical requirement document library, starting from the first historical requirement document whose upload time is closest to the current time, according to the upload time in the document basic information from the most recent to the oldest. When the matching degree between the first target historical requirement document and the second target historical requirement document is greater than the preset matching degree, the matching process of the corresponding first historical requirement document is stopped, and the remaining historical requirement documents are matched with document content to obtain the list of associated requirement documents corresponding to each historical requirement document.

[0109] Specifically, S210 includes: performing word segmentation on the demand summary information to obtain multiple summary words, and obtaining synonyms corresponding to each summary word to obtain summary search terms; using the summary search terms, traversing the document content of each historical demand document to obtain a list of matching demand documents corresponding to each historical demand document, wherein the list of matching demand documents includes historical demand documents that match at least one summary search term; removing historical demand documents in the list of matching demand documents where the number of matching summary search terms is less than a preset threshold to obtain a list of associated demand documents corresponding to each historical demand document.

[0110] In this embodiment, the generation of iterative relationship information is similar to the search of requirement documents. The same algorithm is used for word segmentation, vectorization, and synonym finding for both the requirement summary information and the requirement search statement, further improving the efficiency of requirement information tracing. Specifically, the requirement summary information is segmented using the Jieba word segmentation algorithm to obtain multiple summary word segments. Each summary word segment is then converted into an embedded word vector. Next, the synonyms corresponding to each embedded word vector are obtained using the cosine distance algorithm to obtain the summary search terms.

[0111] In this embodiment, when any historical requirement document contains any summary search term, the historical requirement document is added to the list of matching requirement documents of the historical requirement document corresponding to the summary search term. That is, the list of matching requirement documents includes historical requirement documents that match at least one summary search term.

[0112] In this embodiment, since the noise in the list of matching requirement documents is relatively large, in order to reduce the noise in the list of matching requirement documents, historical requirement documents in the list of matching requirement documents with fewer than a preset number of search terms are deleted, and a list of associated requirement documents corresponding to each historical requirement document is obtained. For example, if the preset number of search terms is 10, then all historical requirement documents in the list of associated requirement documents will have at least 10 search terms matched, but the specific number is not limited.

[0113] S220. Using the uploader information and development object information in the basic document information, classify the list of related requirement documents corresponding to each historical requirement document by development main line to obtain the list of source requirement documents corresponding to each historical requirement document.

[0114] In this implementation, different historical requirement files correspond to different development mainlines. The same development mainline can be used to indicate the same development object or the same uploader, without any specific limitation. For example, historical requirement files of the same business system can be regarded as the same development mainline, and historical requirement files uploaded by the same development team can also be regarded as the same development mainline. By classifying the development mainline of the list of associated requirement documents corresponding to each historical requirement document, a list of source requirement documents corresponding to each historical requirement document can be obtained. That is, the historical requirement documents of the same development mainline corresponding to each historical requirement document. The list of source requirement documents includes multiple source requirement documents.

[0115] S230. Based on the version information and upload time in the basic document information, perform iterative relationship binding on the list of source requirement documents corresponding to each historical requirement document to obtain the iterative relationship information of each historical requirement document.

[0116] In this embodiment, in order to establish the iterative relationship of each historical requirement document in the same source requirement document list, after obtaining the same source requirement document list, the same source requirement document list corresponding to each historical requirement document is sorted according to the version information in the basic document information to obtain a first same source list with development order. Then, according to the upload time in the basic document information, the same source requirement document list corresponding to each historical requirement document is sorted by time to obtain a second same source list with upload time order. Finally, the first same source list and the second same source list are compared to determine the iterative relationship information of each historical requirement document.

[0117] To address the aforementioned technical problems, embodiments of the present invention also provide a traceability device for demand information. Please refer to [link / reference] for details. Figure 4 , Figure 4 This is a schematic diagram of the basic structure of the traceability device for demand information in this embodiment.

[0118] like Figure 4 As shown, a demand information tracing device includes: an acquisition module 1100, a tracing module 1200, a receiving module 1300, a word segmentation module 1400, and a search module 1500. The acquisition module 1100 acquires a pre-set historical demand document library and obtains demand summary information and basic document information corresponding to each historical demand document in the library. The tracing module 1200 performs demand document tracing on each historical demand document based on the demand summary information and the basic document information, and generates iterative relationship information for each historical demand document. The receiving module 1300, upon receiving a demand search request, acquires the search permissions and demand search statement corresponding to the demand search request. The word segmentation module 1400 performs word segmentation on the demand search statement to obtain multiple target words, and acquires synonyms corresponding to each target word to obtain a target search term. The search module 1500 searches for the target demand document corresponding to the target search term according to the search permissions, and obtains a list of historical demand documents that are from the same source as the target demand document based on the iterative relationship information.

[0119] The requirement information tracing device traces the origins of multiple historical requirement documents in the historical requirement document library to determine the iteration relationship information of each historical requirement document. When a requirement search request is received, it finds the most similar target requirement document in the historical requirement document library and obtains a list of historical requirement documents that are from the same source as the target requirement document based on the iteration relationship information, which can improve the efficiency of requirement information tracing.

[0120] In some implementations, the acquisition module is specifically used to: receive a historical requirement document update request, and obtain a preset historical requirement document library through the historical requirement document update request, the historical requirement document library including multiple historical requirement documents; read the basic document information corresponding to each historical requirement document, the basic document information including version information, upload time, uploader information and development object information; and read the formatted content of each historical requirement document through a preset document reading and writing tool to obtain the requirement summary information corresponding to each historical requirement document, the requirement summary information being used to indicate the title formatted text information in the content of the corresponding historical requirement document.

[0121] In some implementations, the tracing module includes: a matching unit, configured to match the document content of each historical requirement document according to the requirement summary information, to obtain a list of associated requirement documents corresponding to each historical requirement document; a classification unit, configured to classify the list of associated requirement documents corresponding to each historical requirement document according to the development main line based on the uploader information and development object information in the document basic information, to obtain a list of source requirement documents corresponding to each historical requirement document; and a binding unit, configured to perform iterative relationship binding on the list of source requirement documents corresponding to each historical requirement document according to the version information and upload time in the document basic information, to obtain iterative relationship information of each historical requirement document.

[0122] In some implementations, the matching unit is specifically used to: perform word segmentation on the demand summary information to obtain multiple summary words, and obtain synonyms corresponding to each summary word to obtain summary search terms; traverse the document content of each historical demand document using the summary search terms to obtain a list of matching demand documents corresponding to each historical demand document, wherein the list of matching demand documents includes historical demand documents that match at least one summary search term; and remove historical demand documents in the list of matching demand documents whose number of matched summary search terms is less than a preset threshold to obtain a list of associated demand documents corresponding to each historical demand document.

[0123] In some implementations, the receiving module is specifically used to: when receiving a demand search request, extract the requester information and demand search statement from the demand search request; search for the level information corresponding to the requester information from preset organizational structure information, and obtain the search permission corresponding to the level information, wherein the search permission is used to indicate the document search scope corresponding to the demand search request.

[0124] In some implementations, the word segmentation module is specifically used to: segment the search query using the Jieba word segmentation algorithm to obtain multiple initial word segments, and filter out stop words from the initial word segments to obtain multiple target word segments; vectorize each target word segment to obtain the embedded word vector corresponding to each target word segment; and obtain the synonyms corresponding to each target word segment from a preset embedded word library using a cosine distance algorithm to obtain the target search term, wherein the target search term is used to indicate the embedded word vector whose cosine distance is less than a preset cosine threshold.

[0125] In some implementations, the search module is specifically used to: traverse the document content of the corresponding historical requirement documents in the historical requirement document library according to the document search range corresponding to the search permission, to obtain candidate requirement documents corresponding to the target search term, wherein the candidate requirement documents are used to indicate historical requirement documents containing the target search term; calculate the target search term hit rate of the candidate requirement documents to obtain the target requirement document with the highest target search term hit rate; obtain a list of source requirement documents corresponding to the target requirement document according to the iteration relationship information, and set the list of source requirement documents corresponding to the target requirement document as the list of historical requirement documents associated with the target requirement document.

[0126] To address the aforementioned technical problems, embodiments of the present invention also provide a computer device. Please refer to [link / reference needed]. Figure 5 , Figure 5 This is a basic structural block diagram of the computer device in this embodiment.

[0127] like Figure 5 The diagram shows the internal structure of a computer device. This computer device includes a processor, non-volatile storage medium, memory, and a network interface connected via a system bus. The non-volatile storage medium stores the operating system, a database, and computer-readable instructions. The database may store control information sequences. When the computer-readable instructions are executed by the processor, they enable the processor to implement a method for tracing demand information. The processor provides computing and control capabilities, supporting the operation of the entire computer device. The memory stores computer-readable instructions, which, when executed by the processor, enable the processor to implement a method for tracing demand information. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0128] In this embodiment, the processor is used to execute... Figure 4 The specific functions of the acquisition module 1100, tracing module 1200, receiving module 1300, word segmentation module 1400, and search module 1500 are described. The memory stores the program code and various types of data required to execute the above modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all sub-modules in the tracing device for demand information. The server can call the server's program code and data to execute the functions of all sub-modules.

[0129] Computer equipment can trace the origins of multiple historical requirement documents in a historical requirement document library to determine the iteration relationship information of each historical requirement document. When a requirement search request is received, the equipment finds the most similar target requirement document in the historical requirement document library and obtains a list of historical requirement documents that are from the same source as the target requirement document based on the iteration relationship information, which can improve the efficiency of requirement information tracing.

[0130] The present invention also provides a computer storage medium in which computer-readable instructions, when executed by one or more processors, cause the one or more processors to perform the steps of the tracing method for demand information of any of the above embodiments.

[0131] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0132] The present invention also provides a computer storage medium in which computer-readable instructions, when executed by one or more processors, cause the one or more processors to perform the steps of the tracing method for demand information of any of the above embodiments.

[0133] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0134] Those skilled in the art will understand that the steps, measures, and solutions in the various operations, methods, and processes discussed in this application can be alternated, modified, combined, or deleted. Furthermore, other steps, measures, and solutions in the various operations, methods, and processes discussed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted. Furthermore, steps, measures, and solutions in the prior art that are similar to those disclosed in this application can also be alternated, modified, rearranged, decomposed, combined, or deleted.

[0135] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for tracing demand information, characterized in that, include: Obtain a pre-set historical requirement document library, and obtain the requirement summary information and basic document information corresponding to each historical requirement document in the historical requirement document library; Based on the requirement summary information and the document basic information, the source of each historical requirement document is traced, and the iteration relationship information of each historical requirement document is generated. This includes: matching the document content of each historical requirement document according to the requirement summary information to obtain a list of associated requirement documents corresponding to each historical requirement document; classifying the list of associated requirement documents corresponding to each historical requirement document according to the development main line through the uploader information and development object information in the document basic information to obtain a list of source requirement documents corresponding to each historical requirement document; sorting the list of source requirement documents corresponding to each historical requirement document according to the development order based on the version information in the document basic information to obtain a first source list with development order; sorting the list of source requirement documents corresponding to each historical requirement document according to the upload time in the document basic information to obtain a second source list with upload time order; and then comparing the first source list and the second source list to determine the iteration relationship information of each historical requirement document. When a demand search request is received, the search permissions and demand search statement corresponding to the demand search request are obtained; The search query is segmented to obtain multiple target words, and the synonyms corresponding to each target word are obtained to obtain the target search terms. According to the search permissions, find the target requirement document corresponding to the target search term, and according to the iteration relationship information, obtain a list of historical requirement documents that are from the same source as the target requirement document.

2. The method for tracing demand information according to claim 1, characterized in that, The step of obtaining a pre-set historical requirement document library and obtaining the requirement summary information and basic document information corresponding to each historical requirement document in the historical requirement document library includes: Receive a historical requirement document update request, and obtain a preset historical requirement document library through the historical requirement document update request, the historical requirement document library including multiple historical requirement documents; Read the basic document information corresponding to each historical requirement document, including version information, upload time, uploader information, and development object information; Using a pre-built document reading and writing tool, the formatted content of each historical requirement document is read to obtain the requirement summary information corresponding to each historical requirement document. The requirement summary information is used to indicate the title formatted text information in the content of the corresponding historical requirement document.

3. The method for tracing demand information according to claim 1, characterized in that, The step of matching the document content of each historical requirement document according to the requirement summary information to obtain the list of associated requirement documents corresponding to each historical requirement document includes: The demand summary information is segmented into words to obtain multiple summary words, and the synonyms corresponding to each summary word are obtained to obtain summary search terms; Using the summary search terms, the document content of each historical requirement document is traversed to obtain a list of matching requirement documents corresponding to each historical requirement document. The list of matching requirement documents includes historical requirement documents that match at least one summary search term. Historical requirement documents with fewer than a preset threshold number of matched summary search terms in the matching requirement document list are removed, resulting in a list of associated requirement documents for each historical requirement document.

4. The method for tracing demand information according to claim 1, characterized in that, The step of obtaining the search permissions and search query corresponding to the request when a search request is received includes: When a demand search request is received, extract the requester information and the demand search statement from the demand search request. The system retrieves the level information corresponding to the requester's information from the preset organizational structure information and obtains the search permissions corresponding to the level information. The search permissions are used to indicate the document search scope corresponding to the request.

5. The method for tracing demand information according to claim 1, characterized in that, The search query is segmented to obtain multiple target words, and the synonyms corresponding to each target word are obtained, resulting in target search terms including: The search query is segmented using the Jieba word segmentation algorithm to obtain multiple initial word segments. Stop words in the initial word segments are then filtered out to obtain multiple target word segments. Each target word segment is vectorized to obtain the embedded word vector corresponding to each target word segment. The cosine distance algorithm is used to obtain the synonyms corresponding to each target word segment from the preset embedding lexicon to obtain the target search term. The target search term is used to indicate the embedding word vectors whose cosine distance is less than a preset cosine threshold.

6. The method for tracing demand information according to any one of claims 1-5, characterized in that, The step of searching for the target requirement document corresponding to the target search term according to the search permissions, and obtaining a list of historical requirement documents that are from the same source as the target requirement document according to the iteration relationship information, includes: Within the document search range corresponding to the search permission, the document content of the corresponding historical requirement documents in the historical requirement document library is traversed to obtain the candidate requirement documents corresponding to the target search term. The candidate requirement documents are used to indicate the historical requirement documents containing the target search term. The target search term hit rate is calculated for the candidate demand documents to obtain the target demand document with the highest target search term hit rate; Based on the iterative relationship information, obtain the list of source requirement documents corresponding to the target requirement document, and set the list of source requirement documents corresponding to the target requirement document as the list of historical requirement documents associated with the target requirement document.

7. A device for tracing demand information, characterized in that, include: The acquisition module is used to acquire a pre-set historical requirement document library, and to acquire the requirement summary information and document basic information corresponding to each historical requirement document in the historical requirement document library; The tracing module is used to trace the origin of each historical requirement document based on the requirement summary information and the document basic information, and to generate iterative relationship information for each historical requirement document. The tracing module includes: a matching unit, used to match the document content of each historical requirement document according to the requirement summary information to obtain a list of associated requirement documents corresponding to each historical requirement document; a classification unit, used to classify the list of associated requirement documents corresponding to each historical requirement document according to the development main line based on the uploader information and development object information in the document basic information to obtain a list of source requirement documents corresponding to each historical requirement document; and a binding unit, used to sort the list of source requirement documents corresponding to each historical requirement document according to the development order based on the version information in the document basic information to obtain a first source list with a development order, and sort the list of source requirement documents corresponding to each historical requirement document according to the upload time in the document basic information to obtain a second source list with an upload time order. The first and second source lists are then compared to determine the iterative relationship information of each historical requirement document. The receiving module is used to obtain the search permissions and search statements corresponding to the search request when it receives a search request. The word segmentation module is used to segment the search query into multiple target words and obtain the synonyms corresponding to each target word to obtain the target search term. The search module is used to search for the target requirement document corresponding to the target search term according to the search permissions, and to obtain a list of historical requirement documents that are from the same source as the target requirement document according to the iteration relationship information.

8. A computer device, characterized in that, The system includes a memory and a processor, wherein the memory stores computer-readable instructions that, when executed by the processor, cause the processor to perform the steps of the tracing method for demand information as described in any one of claims 1 to 6.

9. A computer storage medium, characterized in that, When the computer-readable instructions are executed by one or more processors, the one or more processors perform the steps of the tracing method for demand information as described in any one of claims 1 to 6.

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