A journal keyword determination method, device, medium and product

Abstract

The application discloses a journal keyword determination method, device, medium and product, and relates to the field of data processing. The method comprises the following steps: determining the frequency of each keyword appearing in each document to obtain a first frequency; determining the frequency of all keywords appearing in each document based on the first frequency to obtain a second frequency; determining the frequency of each keyword appearing in all documents based on the first frequency to obtain a third frequency; determining the number of documents in which each keyword appears; determining the field degree of each keyword in each document based on the total number of documents, the first frequency, the second frequency, the third frequency and the number of documents; arranging all extracted keywords in descending order according to the field degree; and extracting multiple keywords from the keyword sequence according to a set condition to serve as journal keywords. The application can accurately determine the keywords of a journal, and can effectively represent the characteristics, key points and research directions of the journal.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, and in particular to a journal keyword determination method, device, medium and product. BACKGROUND

[0002] Keyword is a key task in text mining, which determines keywords representing the theme of the text based on the content of the text. Keyword extraction can help users quickly understand the theme and focus of the text, and help improve the efficiency of information search and the accuracy of information retrieval tasks.

[0003] In a large set of text data, such as a journal paper set, a certain classification paper set, etc., it is also very important to extract the keywords of a certain journal, which helps users quickly understand the characteristics, focus and research direction of the journal. At present, the keywords of the journal mainly depend on the word frequency, but some keywords appear widely and have high frequency, such as calculation, computer, method, development, etc. If these high-frequency or widely distributed words are used as the keywords of a certain journal, it will lead to the inability to effectively represent the characteristics, focus and research direction of the journal. Therefore, how to accurately obtain the keywords to effectively represent the characteristics, focus and research direction of the journal has become a technical problem to be solved by the technical personnel in the field. SUMMARY

[0004] The purpose of the present application is to provide a journal keyword determination method, device, medium and product, which can accurately determine the keywords of the journal, and can effectively represent the characteristics, focus and research direction of the journal.

[0005] To achieve the above purpose, the present application provides the following solutions:

[0006] In a first aspect, the present application provides a journal keyword determination method, comprising:

[0007] Obtaining the total number of journal papers and extracting all keywords of the journal; the keywords are words representing the characteristics of the journal papers; the literature characteristics include the content and theme of the literature;

[0008] Determining the frequency of each keyword appearing in each paper to obtain a first frequency;

[0009] Determining the frequency of all keywords appearing in each paper based on the first frequency to obtain a second frequency;

[0010] Determining the frequency of each keyword appearing in all papers based on the first frequency to obtain a third frequency;

[0011] Determining the number of papers in which each keyword appears;

[0012] determining a field degree of each keyword in each document based on the total number of documents of the journal, the first frequency, the second frequency, the third frequency and the number of documents in which each keyword appears;

[0013] arranging all the extracted keywords in descending order according to the field degrees, to obtain a keyword sequence;

[0014] extracting a plurality of keywords from the keyword sequence according to a set condition, and taking the extracted plurality of keywords as journal keywords.

[0015] Optionally, the determination formula of the second frequency is:

[0016]

[0017] wherein, B j represents the second frequency, A ij represents the first frequency, N represents the total number of extracted keywords in the journal, i represents the ith keyword, and j represents the jth document in the journal.

[0018] Optionally, the determination formula of the third frequency is:

[0019]

[0020] wherein, C i represents the third frequency, A ij represents the first frequency, M represents the total number of documents of the journal, i represents the ith keyword, and j represents the jth document in the journal.

[0021] Optionally, the determination formula of the number of documents in which each keyword appears is:

[0022]

[0023] wherein, D i represents the number of documents in which the keyword i appears, M represents the total number of documents of the journal, and j represents the jth document in the journal; K ij represents whether the keyword i appears in the journal j, when the keyword i appears in the journal j, K ij = 1, and when the keyword i does not appear in the journal j, K ij = 0.

[0024] Optionally, the determination of the field degree of each keyword in each document based on the total number of documents of the journal, the first frequency, the second frequency, the third frequency and the number of documents in which each keyword appears comprises:

[0025] determining a first field degree based on the first frequency, the second frequency and the third frequency;

[0026] determining a second field degree based on the total number of journal literatures, the first frequency, the third frequency and the number of literatures in which each keyword appears;

[0027] determining a field degree of each keyword in each literature based on the first field degree and the second field degree.

[0028] Optionally, the formula for determining the field degree of each keyword in each literature is:

[0029] F ij =F1*F2*100.

[0030] In the formula, F ij represents the field degree of keyword i in literature j, F1 represents the first field degree, and F2 represents the second field degree.

[0031] Optionally, the plurality of keywords are extracted from the keyword sequence according to a set condition, including:

[0032] The top L or top P% keywords are extracted from the keyword sequence.

[0033] In a second aspect, the present application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the journal keyword determination method according to any one of the above embodiments.

[0034] In a third aspect, the present application provides a computer readable storage medium having a computer program stored thereon, wherein the computer program is executable by a processor to implement the steps of the journal keyword determination method according to any one of the above embodiments.

[0035] In a fourth aspect, the present application provides a computer program product, including a computer program executable by a processor to implement the steps of the journal keyword determination method according to any one of the above embodiments.

[0036] According to the specific embodiments provided by the present application, the present application has the following technical effects:

[0037] The present application provides a journal keyword determination method, device, medium and product, by determining the field degree of each keyword in each literature, sorting all keywords in the journal according to the field degree, and then extracting a plurality of keywords from the keyword sequence obtained by sorting according to a set condition as journal keywords, the accurate extraction of keywords can be realized, and the characteristics, focus and research direction of the journal can be effectively represented through the finally obtained keywords. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 A flowchart illustrating a method for determining journal keywords according to an embodiment of this application;

[0040] Figure 2 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] In one exemplary embodiment, this application provides a method for determining journal keywords. This method is executed by a computer device, specifically a terminal or server, or both. In this embodiment, the method is described using an application to a server as an example. Figure 1 As shown, the method for determining journal keywords provided in this application includes:

[0044] Step 100: Obtain the total number of articles in the journal and extract all keywords from the journal. Keywords are words used to characterize the features of articles in the journal. Article features include article content and article topic.

[0045] Step 101: Determine the frequency of each keyword in each document to obtain the first frequency.

[0046] Step 102: Based on the first frequency count, determine the frequency of all keywords appearing in each document to obtain the second frequency count. The formula for determining the second frequency count is:

[0047]

[0048] wherein B j represents the second frequency, i.e. the sum of the frequency of all keywords appearing in document j. A ij represents the first frequency, i.e. the frequency of keyword i appearing in document j. N represents the total number of keywords extracted from the journal, i represents the ith keyword, and j represents the jth document in the journal.

[0049] Step 103: Determine the frequency of each keyword appearing in all documents based on the first frequency, to obtain the third frequency. The determination formula of the third frequency is:

[0050]

[0051] wherein C i represents the third frequency, i.e. the total frequency of keyword i appearing in all documents. M represents the total number of documents in the journal.

[0052] Step 104: Determine the number of documents in which each keyword appears. The determination formula of the number of documents in which each keyword appears is:

[0053]

[0054] wherein D i represents the number of documents in which keyword i appears. K ij represents whether keyword i appears in journal j, wherein when keyword i appears in journal j, K ij = 1, and when keyword i does not appear in journal j, K ij = 0.

[0055] Step 105: Determine the field degree of each keyword in each document based on the total number of documents in the journal, the first frequency, the second frequency, the third frequency, and the number of documents in which each keyword appears.

[0056] Step 106: Arrange all the extracted keywords in descending order according to the field degree, to obtain a keyword sequence.

[0057] Step 107: Extract a plurality of keywords from the keyword sequence according to a set condition, and take the extracted plurality of keywords as the journal keywords.F ij The greater the value of D

[0058] In another exemplary embodiment of the present application, in order to improve the accuracy of the field degree of each keyword in each document, in this embodiment, the implementation process of the above-mentioned step 105 can include:

[0059] (1) determining a first field degree based on the first frequency, the second frequency and the third frequency. The determination formula of the first field degree is:

[0060] F1=A ij / (B j +C i ).

[0061] (2) determining a second field degree based on the total number of journal literatures, the first frequency, the third frequency and the number of literatures in which each keyword appears. The determination formula of the second field degree is:

[0062] F2=log10(M / (D i +C i / A ij )).

[0063] (3) determining the field degree of each keyword in each literature based on the first field degree and the second field degree.

[0064] The determination formula of the field degree of each keyword in each literature is:

[0065] F ij i,j=F1*F2*100.

[0066] In the formula, F ij represents the field degree of keyword i in literature j, F1 represents the first field degree, and F2 represents the second field degree.

[0067] Further, based on the above description, the tuple composed of the keyword and the journal can be represented as E ij :

[0068] E ij =(A ij ,B j ,C i ,D i ,F ij ).

[0069] In summary, the journal keyword determination method provided in the application can effectively identify keywords with high word frequency and wide distribution category.

[0070] In an exemplary embodiment, a computer device is provided, which can be a server or a terminal, and the internal structure diagram thereof can be as shown in Figure 2As shown in the figure. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capability. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store journal keyword determination data. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to realize a journal keyword determination method.

[0071] Those skilled in the art can understand that, Figure 2 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to realize the steps in each of the method embodiments described above.

[0072] In an exemplary embodiment, a computer readable storage medium is provided, storing a computer program, which is executed by a processor to realize the steps in each of the method embodiments described above.

[0073] In an exemplary embodiment, a computer program product is provided, including a computer program, which is executed by a processor to realize the steps in each of the method embodiments described above.

[0074] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0075] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0076] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0077] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, but as long as the combinations of the technical features do not exist, they should be considered as the scope of the present application.

[0078] The principles and implementation modes of the present application are described by applying specific examples herein. The above description of the embodiments is only used to help understand the method and its core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range can be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A method for determining journal keywords, characterized in that, The method for determining journal keywords includes: The total number of documents in the journal is obtained, and all keywords of the journal are extracted; the keywords are words used to characterize the features of the documents in the journal; the document features include the content and the topic of the documents; Determine the frequency of each keyword in each document to obtain the first frequency count; Based on the first frequency count, the frequency count of all keywords appearing in each document is determined to obtain the second frequency count; Based on the first frequency count, the frequency of each keyword appearing in all documents is determined to obtain the third frequency count; Determine the number of documents containing each keyword; The domain degree of each keyword in each document is determined based on the total number of documents in the journal, the first frequency, the second frequency, the third frequency, and the number of documents in which each keyword appears. This includes: determining a first domain degree based on the first frequency, the second frequency, and the third frequency; determining a second domain degree based on the total number of documents in the journal, the first frequency, the third frequency, and the number of documents in which each keyword appears; and determining the domain degree of each keyword in each document based on the first domain degree and the second domain degree. The formula for determining the first domain degree is: F1 = / ( + The formula for determining the second neighborhood degree is: F2 = log10( M / ( + / The formula for determining the domain relevance of each keyword in each document is: In the formula, Keywords i In the literature j The degree of field, Indicates the first domain degree. Indicates the second domain degree. Indicates the first frequency. Indicates the second frequency. Indicates the third frequency. Keywords i The number of documents that appeared M This indicates the total number of articles in the journal; Based on the domain degree, all extracted keywords are sorted in descending order to obtain a keyword sequence; Multiple keywords are extracted from the keyword sequence according to the set conditions, and the extracted keywords are used as journal keywords.

2. The method for determining journal keywords according to claim 1, characterized in that, The formula for determining the second frequency is: ； In the formula, N This represents the total number of keywords extracted from the journal. i This represents the i-th keyword. j This represents the j-th document in the journal.

3. The method for determining journal keywords according to claim 1, characterized in that, The formula for determining the third frequency is: ； In the formula, Indicates the first frequency. i This represents the i-th keyword. j This represents the j-th document in the journal.

4. The method for determining journal keywords according to claim 1, characterized in that, The formula for determining the number of documents containing each keyword is: ； In the formula, j This represents the j-th document in the journal; Keywords i Does it appear in journals and magazines? j When keywords i Appear in periodicals j China Times, When keywords i Not appeared in journals or magazines j China Times, .

5. The method for determining journal keywords according to claim 1, characterized in that, Multiple keywords are extracted from the keyword sequence according to set conditions, including: Extract the top L keywords or the top P% keywords from the keyword sequence.

6. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the journal keyword determination method according to any one of claims 1-5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the journal keyword determination method according to any one of claims 1-5.

8. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the journal keyword determination method according to any one of claims 1-5.

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