CN113779989A - Service requirement text checking method and related equipment - Google Patents
Service requirement text checking method and related equipment Download PDFInfo
- Publication number
- CN113779989A CN113779989A CN202111061516.3A CN202111061516A CN113779989A CN 113779989 A CN113779989 A CN 113779989A CN 202111061516 A CN202111061516 A CN 202111061516A CN 113779989 A CN113779989 A CN 113779989A
- Authority
- CN
- China
- Prior art keywords
- word
- service requirement
- text
- target
- block
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/335—Filtering based on additional data, e.g. user or group profiles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/194—Calculation of difference between files
Abstract
The service requirement text checking method and the related equipment can obtain a target service requirement text; performing phrase blocking on the target service requirement text to obtain at least one first word block; carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block; and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document. The embodiment of the disclosure adopts a natural language processing technology to intelligently analyze the service requirement document specification, automatically check and screen out irregular documents.
Description
Technical Field
The present disclosure relates to the field of text processing technologies, and in particular, to a method and a related device for checking a service requirement text.
Background
The business requirement text is the text which embodies the structuralization of the system requirement and is used for realizing the communication between the business department and the system development team. Currently, the service requirement texts written by service personnel often have irregular problems. For example: and the item numbers, item names and the like in the written service requirement text are not standard. Therefore, how to effectively screen out irregular service requirement documents becomes a problem which needs to be solved urgently by the technical personnel in the field.
Disclosure of Invention
In view of the foregoing problems, the present disclosure provides a method and related device for checking a service requirement text, which overcome or at least partially solve the foregoing problems, and the technical solutions are as follows:
a service requirement text checking method comprises the following steps:
acquiring a target service requirement text;
performing phrase blocking on the target service requirement text to obtain at least one first word block;
carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block;
and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document.
Optionally, the performing phrase blocking on the target service requirement text to obtain at least one first word chunk includes:
and performing phrase blocking on the target service requirement text by using Open NLP to obtain at least one first phrase block, wherein the first phrase block comprises a noun phrase or a verb phrase.
Optionally, the performing deduplication processing on the at least one first word chunk to obtain at least one second word chunk includes:
and performing redundancy calculation on the at least one first word group block, performing duplicate removal on the repeated first word group block, and determining the first word group block reserved after duplicate removal as a second word group block.
Optionally, the preset standard requirement document includes at least one predefined standard word structure template, and the determining whether the target service requirement text is an irregular document by comparing the similarity between the at least one second word chunk and the preset standard requirement document includes:
determining at least one target word structure composed of one or more second word blocks in the at least one second word block;
respectively determining the standard word structure template corresponding to each target word structure in a preset standard requirement document;
for any of the target word structures: comparing the similarity of the target word structure with the corresponding standard word structure template to obtain a similarity result corresponding to the target word structure, and determining whether the target word structure meets the specification according to the similarity result;
and if any target word structure does not meet the specification, determining the target service requirement text as an unnormalized text.
Optionally, the method further includes:
after any target word structure is determined to be not in accordance with the specification, according to one or more second word blocks forming the target word structure, determining a text position of the target word structure in the target service requirement text, and adding a visual mark on the text position of the target service requirement text to obtain a service requirement processing text carrying the visual mark.
Optionally, after the obtaining of the service requirement processing text carrying the visual marker, the method further includes:
and displaying the service requirement processing text.
Optionally, the standard word structure template includes a project number word structure, a project name word structure, and a professional term structure.
A business requirement text inspection device, comprising: a target service requirement text obtaining unit, a phrase block duplicate removal unit and a standard document judgment unit,
the target service requirement text obtaining unit is used for obtaining a target service requirement text;
the phrase blocking unit is used for carrying out phrase blocking on the target service requirement text to obtain at least one first word block;
the word chunk deduplication unit is used for performing deduplication processing on the at least one first word chunk to obtain at least one second word chunk;
and the normative document judging unit is used for comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an unnormalized document.
A computer-readable storage medium, on which a program is stored, which, when being executed by a processor, implements the service requirement text checking method according to any one of the preceding claims.
An electronic device comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to call program instructions in the memory to perform the service requirement text checking method according to any one of the above.
By means of the technical scheme, the service requirement text inspection method and the related equipment can obtain the target service requirement text; performing phrase blocking on the target service requirement text to obtain at least one first word block; carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block; and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document. The embodiment of the disclosure adopts a natural language processing technology to intelligently analyze the service requirement document specification, automatically check and screen out irregular documents.
The foregoing description is only an overview of the technical solutions of the present disclosure, and the embodiments of the present disclosure are described below in order to make the technical means of the present disclosure more clearly understood and to make the above and other objects, features, and advantages of the present disclosure more clearly understandable.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the disclosure. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart illustrating an implementation manner of a service requirement text inspection method according to an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating another implementation of a service requirement text checking method provided by an embodiment of the present disclosure;
fig. 3 is a flowchart illustrating another implementation of a service requirement text checking method provided by an embodiment of the present disclosure;
fig. 4 is a flowchart illustrating another implementation of a service requirement text checking method provided by an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a service requirement text inspection device provided by an embodiment of the present disclosure;
fig. 6 shows a schematic structural diagram of an electronic device provided by an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As shown in fig. 1, a flow diagram of an implementation manner of a service requirement text inspection method provided in an embodiment of the present disclosure may include:
and S100, obtaining a target service requirement text.
The business requirement is a problem to be solved by a user or a condition required for achieving a system target, and is a documentation description for meeting a protocol, standard, specification or other formal customization, that is, a documentation description of a condition or capability required to be met and possessed by a system or a system component.
The business requirement text is the text which embodies the structuralization of the system requirement and is used for realizing the communication between the business department and the system development team. The embodiment of the disclosure can obtain the service requirement text described by the natural language.
Optionally, the service requirement text content provided by the embodiment of the present disclosure may be divided into five parts: the first two sections are introductory, determine the context of the requirements and are described in general terms. The third part is the main body of the text, namely the detailed specification of the requirements, including the relevant contents of business processes, detailed descriptions of functions, non-functional requirements and the like. The last two sections are the appendix and index, including supplementary notes and related notes.
S200, performing phrase blocking on the target service requirement text to obtain at least one first word block.
The embodiment of the disclosure selects the phrase level of the natural language to analyze and block the target service requirement text. And the phrase segmentation is carried out on the target service requirement text on the phrase level, so that the recognition accuracy can be improved, the processing time can be shortened, and the processing efficiency can be improved.
Specifically, based on the method shown in fig. 1 and as shown in fig. 2, a flowchart of another implementation manner of the service requirement text inspection method provided in the embodiment of the present disclosure is schematically shown, and step S200 may include:
s210, performing phrase blocking on the target service requirement text by using Open NLP to obtain at least one first word block.
Natural Language Processing (NLP) is an important direction in the fields of computer science and artificial intelligence. It studies various theories and methods that enable efficient communication between humans and computers using natural language. The computer accepts the input of the user in the form of natural language, and internally carries out a series of operations such as processing, calculation and the like through a human-defined algorithm so as to simulate the understanding of human beings on the natural language and return a result expected by the user.
The embodiment of the disclosure can use the chunker of the Open source tool Open NLP to perform phrase segmentation on the target service requirement text to obtain at least one first word chunk. Word chunks are descriptions of a phrase hierarchy. The first phrase block may include a noun phrase or a verb phrase.
S300, carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block.
The repeated first word blocks can be deduplicated, only one first word block can be reserved for the repeated first word blocks, and the reserved first word blocks are determined as second word blocks. The embodiment of the disclosure can reduce the phrase blocks to be queried and improve the query rate through the duplicate removal processing.
Optionally, based on the method shown in fig. 1, as shown in fig. 3, a flowchart of another implementation manner of the service requirement text inspection method provided in the embodiment of the present disclosure is shown, and step S300 may include:
s310, performing redundancy calculation on at least one first phrase block, performing duplicate removal on the repeated first phrase block, and determining the first phrase block reserved after duplicate removal as a second phrase block.
Specifically, the embodiment of the present disclosure may perform redundancy calculation on at least one first word block through an automatic detection algorithm in the NLP.
S400, comparing the similarity of at least one second word block and a preset standard requirement document, and determining whether the target service requirement document is an irregular document.
Optionally, the preset standard requirement document includes at least one predefined standard term structure template. Optionally, the standard word structure template includes a project number word structure, a project name word structure, and a professional term structure.
It can be understood that the standard requirement document can be set according to actual requirements, and when the requirement specification is changed, only the standard word structure template in the standard requirement document needs to be adjusted.
Optionally, based on the method shown in fig. 3, as shown in fig. 4, a flowchart of another implementation manner of the service requirement text inspection method provided in the embodiment of the present disclosure is shown, and step S400 may include:
s410, in at least one second word block, determining at least one target word structure composed of one or more second word blocks.
And S420, respectively determining a standard word structure template corresponding to each target word structure in the preset standard requirement document.
S430, for any target word structure: and comparing the similarity of the target word structure with the corresponding standard word structure template to obtain a similarity result corresponding to the target word structure, and determining whether the target word structure meets the specification according to the similarity result.
S440, if the structures of the target words meet the specification, determining the target service requirement text as a specification document.
S450, if any target word structure does not meet the specification, determining the target service requirement text as an unnormalized text.
For ease of understanding, the description is made herein by way of example: suppose the project number word structure in the standard word structure template is "nong-silver department XXXX No. XXX". If the target word structure is 'Nongyin Do 2020 No. 123456', the target word structure meets the specification. If the target word structure is 'Nongyin Dow.2020 No. 123456', the target word structure does not meet the specification.
Optionally, after determining that any target word structure does not meet the specification, the embodiment of the present disclosure may determine, according to one or more second word blocks constituting the target word structure, a text position of the target word structure in the target service requirement text, and add a visual marker to the text position of the target service requirement text, to obtain a service requirement processing text carrying the visual marker.
Optionally, the embodiment of the present disclosure may display the service requirement processing text.
The service requirement text inspection method provided by the disclosure can obtain a target service requirement text; performing phrase blocking on the target service requirement text to obtain at least one first word block; carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block; and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document. The embodiment of the disclosure adopts a natural language processing technology to intelligently analyze the service requirement document specification, automatically check and screen out irregular documents.
Although the operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order, and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
Corresponding to the foregoing method embodiment, an embodiment of the present disclosure further provides a service requirement text checking device, whose structure is shown in fig. 5, and may include: a target service requirement text obtaining unit 100, a phrase blocking unit 200, a phrase block duplication removing unit 300 and a standard document judging unit 400.
A target service requirement text obtaining unit 100, configured to obtain a target service requirement text.
And a phrase blocking unit 200, configured to perform phrase blocking on the target service requirement text to obtain at least one first word block.
Optionally, the phrase blocking unit 200 is specifically configured to perform phrase blocking on the target service requirement text by using Open NLP to obtain at least one first phrase block, where the first phrase block includes a noun phrase or a verb phrase.
A word chunk de-duplication unit 300, configured to perform de-duplication processing on at least one first word chunk to obtain at least one second word chunk.
Optionally, the phrase block duplicate removal unit 300 is specifically configured to perform redundancy calculation on at least one first phrase block, perform duplicate removal on repeated first phrase blocks, and determine a first phrase block remaining after the duplicate removal as a second phrase block.
And the normative document judging unit 400 is used for comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an unnormalized document.
Optionally, the preset standard requirement document includes at least one predefined standard term structure template. Optionally, the standard word structure template includes a project number word structure, a project name word structure, and a professional term structure.
Optionally, the canonical document judgment unit 400 includes: the system comprises a target word structure determining subunit, a standard word structure template determining subunit, a target word structure standard judging subunit, a standard text determining subunit and an unnormalized text determining subunit.
And the target word structure determining subunit is used for determining at least one target word structure formed by one or more second word blocks in the at least one second word block.
And the standard word structure template determining subunit is used for respectively determining the standard word structure templates corresponding to the target word structures in the preset standard requirement document.
And the target word structure standard judgment subunit is used for judging the structure of any target word: and comparing the similarity of the target word structure with the corresponding standard word structure template to obtain a similarity result corresponding to the target word structure, and determining whether the target word structure meets the specification according to the similarity result.
And the standard text determining subunit is used for determining the target service requirement text as a standard document if the structures of all the target words meet the standard.
And the unnormalized text determining subunit is used for determining the target service requirement text as an unnormalized text if any target word structure is not in accordance with the specification.
Optionally, the service requirement text checking apparatus may further include: the service requirement processing text obtaining unit.
And the service requirement processing text obtaining unit is used for determining the text position of the target word structure in the target service requirement text according to one or more second word blocks forming the target word structure after determining that any target word structure is not in accordance with the standard, and adding a visual mark on the text position of the target service requirement text to obtain the service requirement processing text carrying the visual mark.
Optionally, the service requirement text checking apparatus may further include: and a text display unit.
And the text display unit is used for displaying the service requirement processing text after the service requirement processing text acquisition unit acquires the service requirement processing text carrying the visual mark.
The service requirement text inspection device provided by the disclosure can obtain a target service requirement text; performing phrase blocking on the target service requirement text to obtain at least one first word block; carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block; and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document. The embodiment of the disclosure adopts a natural language processing technology to intelligently analyze the service requirement document specification, automatically check and screen out irregular documents.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The service requirement text checking device comprises a processor and a memory, wherein the target service requirement text obtaining unit 100, the phrase partitioning unit 200, the phrase block deduplication unit 300, the specification document judgment unit 400 and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, the natural language processing technology is adopted by adjusting the kernel parameters, the business requirement document specification is intelligently analyzed, the examination is automatically carried out, and the irregular documents are screened out.
The disclosed embodiments provide a computer-readable storage medium on which a program is stored, which when executed by a processor implements the business requirement text inspection method.
The embodiment of the disclosure provides a processor, which is used for running a program, wherein the method for checking a service requirement text is executed when the program runs.
As shown in fig. 6, an embodiment of the present disclosure provides an electronic device 1000, where the electronic device 1000 includes at least one processor 1001, and at least one memory 1002 and a bus 1003 connected to the processor 1001; the processor 1001 and the memory 1002 complete communication with each other through the bus 1003; the processor 1001 is configured to call program instructions in the memory 1002 to execute the service requirement text checking method described above. The electronic device herein may be a server, a PC, a PAD, a mobile phone, etc.
The present disclosure also provides a computer program product adapted to perform a program of initializing a text inspection method steps in service need when executed on an electronic device.
The present disclosure is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus, electronic devices (systems), and computer program products according to embodiments of the disclosure. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, an electronic device includes one or more processors (CPUs), memory, and a bus. The electronic device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
In the description of the present disclosure, it is to be understood that the directions or positional relationships indicated as referring to the terms "upper", "lower", "front", "rear", "left" and "right", etc., are based on the directions or positional relationships shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the positions or elements referred to must have specific directions, be constituted and operated in specific directions, and thus, are not to be construed as limitations of the present disclosure.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present disclosure may be provided as a method, system, or computer program product. Accordingly, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The above are merely examples of the present disclosure, and are not intended to limit the present disclosure. Various modifications and variations of this disclosure will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure should be included in the scope of the claims of the present disclosure.
Claims (10)
1. A service requirement text checking method is characterized by comprising the following steps:
acquiring a target service requirement text;
performing phrase blocking on the target service requirement text to obtain at least one first word block;
carrying out duplicate removal processing on the at least one first word group block to obtain at least one second word group block;
and comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an irregular document.
2. The method of claim 1, wherein the performing phrase blocking on the target service requirement text to obtain at least one first word block comprises:
and performing phrase blocking on the target service requirement text by using Open NLP to obtain at least one first phrase block, wherein the first phrase block comprises a noun phrase or a verb phrase.
3. The method of claim 1, wherein the de-duplicating the at least one first word chunk to obtain at least one second word chunk comprises:
and performing redundancy calculation on the at least one first word group block, performing duplicate removal on the repeated first word group block, and determining the first word group block reserved after duplicate removal as a second word group block.
4. The method according to claim 1, wherein the preset standard requirement document includes at least one predefined standard word structure template, and the determining whether the target service requirement text is an irregular document by comparing the similarity between the at least one second word block and the preset standard requirement document includes:
determining at least one target word structure composed of one or more second word blocks in the at least one second word block;
respectively determining the standard word structure template corresponding to each target word structure in a preset standard requirement document;
for any of the target word structures: comparing the similarity of the target word structure with the corresponding standard word structure template to obtain a similarity result corresponding to the target word structure, and determining whether the target word structure meets the specification according to the similarity result;
and if any target word structure does not meet the specification, determining the target service requirement text as an unnormalized text.
5. The method of claim 4, further comprising:
after any target word structure is determined to be not in accordance with the specification, according to one or more second word blocks forming the target word structure, determining a text position of the target word structure in the target service requirement text, and adding a visual mark on the text position of the target service requirement text to obtain a service requirement processing text carrying the visual mark.
6. The method of claim 5, wherein after the obtaining the business requirement handling text carrying the visual marker, the method further comprises:
and displaying the service requirement processing text.
7. The method of claim 4, wherein the standard word structure template comprises an item number word structure, an item name word structure, and a professional term structure.
8. A service requirement text checking apparatus, comprising: a target service requirement text obtaining unit, a phrase block duplicate removal unit and a standard document judgment unit,
the target service requirement text obtaining unit is used for obtaining a target service requirement text;
the phrase blocking unit is used for carrying out phrase blocking on the target service requirement text to obtain at least one first word block;
the word chunk deduplication unit is used for performing deduplication processing on the at least one first word chunk to obtain at least one second word chunk;
and the normative document judging unit is used for comparing the similarity of the at least one second word block with a preset standard requirement document to determine whether the target service requirement document is an unnormalized document.
9. A computer-readable storage medium, on which a program is stored, which, when being executed by a processor, implements the service requirement text checking method according to any one of claims 1 to 7.
10. An electronic device comprising at least one processor, and at least one memory connected to the processor, a bus; the processor and the memory complete mutual communication through the bus; the processor is configured to invoke program instructions in the memory to perform the business requirement text checking method of any of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111061516.3A CN113779989A (en) | 2021-09-10 | 2021-09-10 | Service requirement text checking method and related equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111061516.3A CN113779989A (en) | 2021-09-10 | 2021-09-10 | Service requirement text checking method and related equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113779989A true CN113779989A (en) | 2021-12-10 |
Family
ID=78842287
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111061516.3A Pending CN113779989A (en) | 2021-09-10 | 2021-09-10 | Service requirement text checking method and related equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113779989A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115203506A (en) * | 2022-06-27 | 2022-10-18 | 海南电网有限责任公司信息通信分公司 | Archive filing similarity calculation method based on multi-mode verification algorithm |
-
2021
- 2021-09-10 CN CN202111061516.3A patent/CN113779989A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115203506A (en) * | 2022-06-27 | 2022-10-18 | 海南电网有限责任公司信息通信分公司 | Archive filing similarity calculation method based on multi-mode verification algorithm |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9542477B2 (en) | Method of automated discovery of topics relatedness | |
| CN108470040B (en) | Method and device for warehousing unstructured data | |
| US20160012082A1 (en) | Content-based revision history timelines | |
| US9406018B2 (en) | Systems and methods for semantic data integration | |
| CN107203529B (en) | Multi-service relevance analysis method and device based on metadata graph structure similarity | |
| CN108170656A (en) | Template establishment method, document creating method, rendering intent and device | |
| CN112328544B (en) | Multidisciplinary simulation data classification method, device and storage medium | |
| CN111125116B (en) | Method and system for positioning code field in service table and corresponding code table | |
| Luciv et al. | Detecting near duplicates in software documentation | |
| CN109445778A (en) | A kind of method and apparatus that the interface auxiliary based on SVG file generates | |
| CN105117489B (en) | Database management method and device and electronic equipment | |
| CN112307303A (en) | Efficient and accurate network page duplicate removal system based on cloud computing | |
| CN113779989A (en) | Service requirement text checking method and related equipment | |
| CN111221698A (en) | Task data acquisition method and device | |
| CN112069808A (en) | Financing wind control method and device, computer equipment and storage medium | |
| US20210097055A1 (en) | System having a content consistency service for a collaboration tool | |
| CN111475641B (en) | Data extraction method and device, storage medium and equipment | |
| CN114416840A (en) | Data acquisition method and device combining RPA and AI, server and storage medium | |
| US20210334238A1 (en) | Automated file naming and file organization using machine learning | |
| CN112836033A (en) | Business model management method, device, equipment and storage medium | |
| Rauber et al. | Repeatability and Re-usability in Scientific Processes: Process Context, Data Identification and Verification. | |
| CN110727672A (en) | Data mapping relation query method and device, electronic equipment and readable medium | |
| US10803026B1 (en) | Dynamic directory recommendation and management | |
| CN114416174A (en) | Model reconstruction method and device based on metadata, electronic equipment and storage medium | |
| Verma et al. | Analysis and implementation of data mining algorithms for deploying ID3, CHAID and Naive Bayes for random dataset |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |