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Method for constructing accounting term co-occurrence network diagram

A network graph and accounting technology, applied in the creation of semantic tools, computing, semantic analysis, etc., can solve the problems of small scale of semantic materials, few cross-domain research results, lack of semantic features, etc., to achieve a large range of knowledge and ensure comprehensiveness and scientific, to ensure the effect of expression efficiency

Inactive Publication Date: 2022-01-11
JINAN UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, this research method is limited by the selected semantic materials. Among them, the semantic data processed by the linguistics-based extraction method is small, while the statistics-based and machine learning-based methods can handle large-scale texts, but the extracted terms There is a lot of noise, the domain characteristics are not prominent, and the semantic characteristics are lacking
[0008] 2. Insufficient fit with domain knowledge
[0010] 3. The research perspective is single, and there are few cross-field research results
[0011] In the existing research, more concepts are extracted from the keywords of the text materials, and the research process is to remove redundant information from the text materials, which makes the research perspective relatively single, and there are few cross-field research results

Method used

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  • Method for constructing accounting term co-occurrence network diagram
  • Method for constructing accounting term co-occurrence network diagram
  • Method for constructing accounting term co-occurrence network diagram

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Experimental program
Comparison scheme
Effect test

Embodiment

[0076] Simulation

[0077] The present invention uses "English-Chinese Modern Accounting Dictionary" edited by Chen Jinchi of China Financial and Economic Publishing House in 2009 as the experimental data, from which 4289 accounting terms and 32086 terms are sorted out as the experimental text in the accounting field.

[0078] The main programs and software used to process data here are: Excel2016, Python3.7, MATLAB R2016a, etc., among which Excel is used for the structural arrangement of accounting dictionaries, and the definition of terms is segmented using Python’s jieba package, and drawn based on MATLAB Directed cycle graph and calculate PageRank value. The specific work is as follows:

[0079] (1) Manually extract and organize the definition text of accounting terms.

[0080] According to the text analysis of the accounting dictionary above, in the dictionary, there are not only definitional descriptions for the interpretation of an accounting term, but also non-defini...

Embodiment 2

[0112] Verify the effectiveness of the present invention

[0113] The model proposed by the present invention is used to extract the semantic primitives in the accounting field. By constructing a directed network graph for the accounting dictionary, the improved PageRank algorithm, namely the PRFR algorithm, is used to extract the semantic primitives and describe the domain knowledge, and then merge based on the synonym forest , to obtain the candidate set of the final semantic primitives, and compare and analyze the method based on word frequency and the method based on TF-IDF as a benchmark experiment.

[0114] (1) Method based on word frequency

[0115] The method based on word frequency counts the occurrence frequency of terms and ranks the terms according to the frequency. The top 50 terms are taken as the semantic primitives in the accounting field, as shown in Table 4.

[0116] Table 4 Semantic primitive extraction based on word frequency method

[0117]

[0118] ...

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Abstract

The invention discloses a method for constructing an accounting term co-occurrence network diagram, which comprises the following steps of: extracting semantic primitives of an accounting field, namely constructing a directed network diagram for vocabularies in an accounting dictionary, extracting the semantic primitives and describing field knowledge by utilizing an improved PageRank algorithm, and then combining based on synonym forest to finally obtain a candidate set of the semantic primitives of the accounting terms. The semantic primitive extraction method based on the graph theory is designed for the corpus of the accounting dictionary by utilizing the characteristics of knowledge in the accounting field. The accounting dictionary serves as an important professional corpus and an authoritative specification text in the accounting field, and systematically and comprehensively covers related terms and definitions thereof in the accounting field. If a computer can 'read' an accounting text by means of the semantic primitives extracted from the accounting dictionary, a large amount of information in the accounting field can be effectively utilized, so that term research based on the accounting dictionary effectively breaks through subjective analysis and small sample data limitation in semantic primitive extraction.

Description

technical field [0001] The invention relates to the technical field of computer readability of financial information, in particular to a method for constructing an accounting term co-occurrence network graph. [0002] technical background [0003] At present, online financial reports in the accounting field lack standardized knowledge descriptions, so difficulties are encountered in solving computer readability of financial information, which hinders the use and development prospects of XBRL and other online financial reports. At present, a few scholars try to solve the difficulty of semantic primitive extraction based on the current popular machine learning algorithms. Although these methods effectively reduce labor and time costs, the extracted terms have a lot of noise, the domain characteristics are not prominent, and their effectiveness cannot be verified. The research of the present invention fills up the research blank of network financial reports, studies the key issu...

Claims

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Application Information

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IPC IPC(8): G06F40/289G06F40/216G06F16/36G06F40/30
CPCG06F40/289G06F40/216G06F40/30G06F16/367
Inventor 潘定梁倬骞叶迪
Owner JINAN UNIVERSITY
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