Keyword extension method and device and storage medium

Abstract

The embodiment of the invention provides a keyword extension method and device and a storage medium, and the method comprises the steps that after a retrieval result of a first keyword is obtained, a co-occurrence extension word is determined according to the retrieval result and the first keyword; according to the co-occurrence expansion word, a second keyword is determined, and the second keyword is used for retrieval again. The technical scheme provided by the invention is used for solving the problem that the technical scheme behind the keyword is not considered in the extension of the keyword in the prior art.

Description

Technical Field

[0001] This document relates to the field of patent search technology, and in particular to a method, apparatus and storage medium for expanding keywords. Background Technology

[0002] In the patent search process, the selection of keywords is crucial, so how to choose keywords has become a topic of concern.

[0003] In existing technologies, alternative keywords are typically provided to users based on semantic analysis and a pre-set thesaurus.

[0004] However, the aforementioned keyword expansion does not consider the underlying technical solutions, thus the expanded keywords lack specificity. Search results obtained using non-targeted keywords will inevitably fail to meet user needs, thereby reducing user search efficiency. Summary of the Invention

[0005] Based on the above analysis, this application aims to propose a keyword expansion method, apparatus, and storage medium to improve users' retrieval efficiency.

[0006] In a first aspect, one or more embodiments of this specification provide a method for expanding keywords, including: after obtaining the search results of a first keyword, determining co-occurring expanded words based on the search results and the first keyword;

[0007] Based on the co-occurring extended words, a second keyword is determined, which is then used for further retrieval.

[0008] Further, the co-occurring extended words and synonym extended words determined based on the search results and the first keyword include:

[0009] Based on the search results, the target file is determined;

[0010] Based on the target file, determine the co-occurring extended words of the first keyword.

[0011] Furthermore, the first keyword includes: nouns;

[0012] The step of determining the target file based on the search results includes:

[0013] Determine the frequency of occurrence of nouns in the first keyword in each file of the search results;

[0014] Files whose frequency of occurrence of the term reaches a preset threshold are identified as the target files.

[0015] Further, determining the co-occurring extended words of the first keyword based on the target file includes:

[0016] In the target file, identify the nouns that co-occur with the first keyword;

[0017] Co-occurring nouns whose frequency exceeds a preset threshold are identified as co-occurring extended words of the first keyword.

[0018] Further, determining the co-occurring extended words of the first keyword based on the target file includes:

[0019] In the target file, based on the co-occurring nouns identified as the co-occurring extended words, the co-occurring verbs of the first keyword are determined through speech analysis;

[0020] The co-occurring verbs of the first keyword are identified as the co-occurring extended words.

[0021] Further, the co-occurring extended terms determined based on the search results and the first keyword include:

[0022] Based on the search results, the target file is determined;

[0023] Based on the target file and the first keyword, determine the target keywords;

[0024] Based on the target keywords, the co-occurring extended terms are determined from the search results.

[0025] Further, determining the target keywords based on the target file and the first keyword includes:

[0026] Based on semantic analysis, keywords are extracted from the target file;

[0027] Determine the similarity between the keywords of the target file and the first keyword;

[0028] The keywords of the target files whose similarity reaches the threshold are determined as the target keywords.

[0029] Further, determining the co-occurring extended terms from the search results based on the target keyword includes:

[0030] Based on the target keywords, determine the file set from the search results;

[0031] Within the document set, identify the nouns that co-occur with the target keyword;

[0032] Co-occurring nouns whose frequency exceeds a preset threshold are identified as the co-occurring extended words;

[0033] Based on the nouns that are identified as co-occurring extended words, the verbs that co-occur with the target keywords are determined through speech analysis.

[0034] The co-occurring verbs of the target keyword are identified as the co-occurring extended words.

[0035] Secondly, embodiments of this application provide a keyword expansion device, including: an expansion module and a determination module;

[0036] The extension module is used to determine co-occurring extended words based on the search results of the first keyword and the first keyword after obtaining the search results of the first keyword.

[0037] The determining module is used to determine a second keyword based on the co-occurring extended words, and the second keyword is used for further retrieval.

[0038] Thirdly, embodiments of this application provide a storage medium, including:

[0039] Used to store computer-executable instructions, which, when executed, implement the method described in any one of the first aspects.

[0040] Compared with the prior art, this application can achieve at least the following technical effects:

[0041] During the search process, the user's initial search query does not fully display all the features of the technical solution. These terms usually exist in other parts of the solution and co-occur with the keywords in the initial search query. To find these keywords, this application determines co-occurring extended terms based on existing search results and the first keyword. Then, based on the user's instructions, a second keyword is determined according to the co-occurring extended terms to achieve automatic keyword expansion, thereby improving the user's search efficiency. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 A flowchart illustrating a keyword expansion method provided for one or more embodiments of this specification;

[0044] Figure 2 A flowchart illustrating another method for expanding keywords provided in one or more embodiments of this specification. Detailed Implementation

[0045] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0046] Users often encounter the following situations when conducting patent searches:

[0047] Scenario 1: After entering keywords, the user receives numerous search results, many of which are related to the searched solution. In this case, the user needs to spend a significant amount of time reviewing the search results for patents or patent applications related to the searched solution, and then selecting new keywords based on these patents or patent applications.

[0048] Scenario 2: After entering keywords, users receive numerous search results, but few documents are directly related to the searched solution. A user may find a patent or patent application relevant to the searched solution, but the patent or patent application is lengthy and not easily readable, causing the user to spend a significant amount of time studying the technical solutions within the patent or patent application to expand their keyword search.

[0049] To address the aforementioned scenario, this application leverages the co-occurrence relationship between words in text. After obtaining the search results for the first keyword, it determines co-occurrence expansion words based on the search results and the first keyword. Based on the co-occurrence expansion words, a second keyword is determined, which is then used for further retrieval. The co-occurrence expansion words are keywords obtained based on co-occurrence relationships.

[0050] Specifically, for scenario 1, this application embodiment provides a keyword expansion method, such as... Figure 1 As shown, it includes the following steps:

[0051] Step A1: Determine the target file based on the search results.

[0052] In this application embodiment, in scenario 1, since users need to spend a lot of time finding relevant patents, it is necessary to traverse all patents or patent applications in the search results to determine the target file.

[0053] Specifically, the frequency of the first keyword in each file in the search results is determined. Files whose term frequency reaches a preset threshold are identified as target files. Patent or patent application writing conventions emphasize consistency in naming. That is, the same term is used only once in the same patent or patent application. Therefore, it is highly likely that the terms related to the core solution in a patent or patent application will appear multiple times. Thus, if the frequency of the first keyword in a patent or patent application is insufficient, it indicates that the patent or patent application is not what the user is looking for. Conversely, if the frequency of the first keyword in a patent or patent application reaches the preset threshold, it indicates that the patent or patent application is a target file.

[0054] Step A2: Based on the target file, determine the co-occurring extended words of the first keyword.

[0055] In scenario 1, there are many documents related to the searched solution in the search results, indicating that the first keyword is reasonable. In this case, co-occurring extended terms can be determined directly based on the first keyword.

[0056] Specifically, based on their parts of speech, co-occurring extended words are divided into nouns and verbs.

[0057] For nouns, in the target file, identify the co-occurring nouns of the first keyword; identify the co-occurring nouns whose frequency exceeds a preset threshold as co-occurring extended words of the first keyword.

[0058] In practice, the text distance between the primary keyword and co-occurring nouns can be limited. For example, when using co-occurrence analysis, the word count between the primary keyword and co-occurring nouns can be specified, and the primary keyword and co-occurring nouns must be in the same sentence. This approach can increase the effectiveness of the expanded keywords.

[0059] For verbs, in the target file, based on the co-occurring nouns identified as co-occurring extended words, the co-occurring verbs of the first keyword are determined through speech analysis; these co-occurring verbs of the first keyword are then identified as co-occurring extended words. In patents or patent applications, nouns are usually repeated, while verbs are not necessarily repeated. However, verbs usually correspond to a subject or object, meaning that a co-occurring noun may have a corresponding verb. During retrieval, the keywords in the vast majority of search queries are verbs and nouns; therefore, through speech analysis, the co-occurring verbs of the first keyword are determined, and these co-occurring verbs are used as extended keywords.

[0060] Step A3: Determine the second keyword based on co-occurring extended words.

[0061] In this embodiment of the application, the second keyword is used for further retrieval. That is, the user can select the next round of search keywords from the second keyword.

[0062] For scenario 2, this application provides another method for expanding keywords, such as... Figure 2 As shown, it includes the following steps:

[0063] Step B1: Determine the target file based on the search results.

[0064] In this embodiment of the application, since the user has found a desired patent or patent application, the target file is specified by the user himself.

[0065] Step B2: Determine the target keywords based on the target document and the primary keyword.

[0066] In this embodiment, Scenario 2 illustrates that the user's general direction in selecting keywords is correct, but there are some deviations in the details. Therefore, it is necessary to expand the keywords based on the target file. Specifically, based on semantic analysis, keywords are extracted from the target file; the similarity between the keywords in the target file and the first keyword is determined; and the keywords in the target file whose similarity reaches a threshold are identified as target keywords.

[0067] It should be noted that the target file will extract multiple keywords, but these keywords are given according to their frequency of occurrence. Therefore, there will be some words that are irrelevant to the technical solution, such as "the described". To remove such words, we need to use the first keyword as a word vector, and then use the keywords in the target file to form another word vector. Then, we calculate the cosine similarity between the two word vectors. When the cosine similarity reaches a threshold, all words in the corresponding word vector of the target file are considered target keywords.

[0068] Step B3: Based on the target keywords, determine the co-occurring extended terms from the search results.

[0069] In this embodiment, multiple word vectors can be constructed using the keywords of the proposed target file. After detecting the cosine similarity between all word vectors and the first keyword, a certain number of target keywords are obtained. These target keywords are then used for keyword expansion. The specific process is as follows:

[0070] Based on the target keywords, a set of documents is determined from the search results; within the set of documents, co-occurring nouns of the target keywords are identified; co-occurring nouns with a frequency greater than a preset threshold are identified as co-occurring extended words; based on the co-occurring nouns identified as co-occurring extended words, co-occurring verbs of the target keywords are identified based on speech analysis; and co-occurring verbs of the target keywords are identified as co-occurring extended words.

[0071] Using the method described above, the first keyword is expanded using keywords from the target file in Scenario 2. Then, a second expansion is performed on the target keyword. Through these two expansions, expanded keywords can be quickly provided to the user in Scenario 2.

[0072] Step B4: Determine the second keyword based on co-occurring extended words.

[0073] In this embodiment of the application, the second keyword is used for further retrieval. That is, the user can select the next round of search keywords from the second keyword.

[0074] This application provides a keyword expansion device, including: an expansion module and a determination module;

[0075] The extension module is used to determine co-occurring extended words based on the search results of the first keyword and the first keyword after obtaining the search results of the first keyword.

[0076] The determining module is used to determine a second keyword based on the co-occurring extended words, and the second keyword is used for further retrieval.

[0077] This application provides a storage medium, including:

[0078] Used to store computer-executable instructions, which, when executed, implement the method described in any of the above embodiments.

[0079] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0080] In the 1930s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement to the methodology cannot be implemented using a hardware physical module. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program a digital system themselves to "integrate" it onto a PLD, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0081] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0082] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0083] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0084] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification 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, etc.) containing computer-usable program code.

[0085] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0089] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0090] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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 technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0091] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0092] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0093] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0094] The above description is merely an embodiment of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A method for expanding keywords, characterized in that, include: After obtaining the search results for the first keyword, co-occurring extended terms are determined based on the search results and the first keyword; Based on the co-occurring extended words, a second keyword is determined, which is then used for further retrieval.

2. The method according to claim 1, characterized in that, The co-occurring extended words and synonym extended words determined based on the search results and the first keyword include: Based on the search results, the target file is determined; Based on the target file, determine the co-occurring extended words of the first keyword.

3. The method according to claim 2, characterized in that, The first keyword includes: nouns; The step of determining the target file based on the search results includes: Determine the frequency of occurrence of nouns in the first keyword in each file of the search results; Files whose frequency of occurrence of the term reaches a preset threshold are identified as the target files.

4. The method according to claim 2, characterized in that, The step of determining the co-occurring extended words of the first keyword based on the target file includes: In the target file, identify the nouns that co-occur with the first keyword; Co-occurring nouns whose frequency exceeds a preset threshold are identified as co-occurring extended words of the first keyword.

5. The method according to claim 4, characterized in that, The step of determining the co-occurring extended words of the first keyword based on the target file includes: In the target file, based on the co-occurring nouns identified as the co-occurring extended words, the co-occurring verbs of the first keyword are determined through speech analysis; The co-occurring verbs of the first keyword are identified as the co-occurring extended words.

6. The method according to claim 1, characterized in that, The co-occurring extended terms determined based on the search results and the first keyword include: Based on the search results, the target file is determined; Based on the target file and the first keyword, determine the target keywords; Based on the target keywords, the co-occurring extended terms are determined from the search results.

7. The method according to claim 6, characterized in that, The step of determining the target keywords based on the target file and the first keyword includes: Based on semantic analysis, keywords are extracted from the target file; Determine the similarity between the keywords of the target file and the first keyword; The keywords of the target files whose similarity reaches the threshold are determined as the target keywords.

8. The method according to claim 6, characterized in that, The step of determining the co-occurring extended terms from the search results based on the target keyword includes: Based on the target keywords, determine the file set from the search results; Within the document set, identify the nouns that co-occur with the target keyword; Co-occurring nouns whose frequency exceeds a preset threshold are identified as the co-occurring extended words; Based on the nouns that are identified as co-occurring extended words, the verbs that co-occur with the target keywords are determined through speech analysis. The co-occurring verbs of the target keyword are identified as the co-occurring extended words.

9. A keyword expansion device, characterized in that, include: Extended modules and defined modules; The extension module is used to determine co-occurring extended words based on the search results of the first keyword and the first keyword after obtaining the search results of the first keyword. The determining module is used to determine a second keyword based on the co-occurring extended words, and the second keyword is used for further retrieval.

10. A storage medium, characterized in that, include: Used to store computer-executable instructions, which, when executed, implement the method of any one of claims 1-8.

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