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| Research on Core Word Extraction Algorithm Based on Contextual Concept |
| Shi Jin1, Han Jin2, Zhao Xiaoke1, Liu Qianli1 |
1.School of Information Management, Nanjing University, Nanjing 210023
2.Col1ege of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044 |
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Abstract As there has been little domestic or international research on the context core word extraction algorithm—researchers have mainly focused on the keyword extraction algorithm—this paper proposes a context-based dependency grammar analysis algorithm. Right at the outset, this paper proves the equivalency of the dependency parsing problem to the splitting of a sentence to obtain the minimum scale context and to find the core words in the minimum scale context. In order to solve these problems, this paper proposes two context core word solvingthe context core word extraction algorithm based on entropy comparison; and the context core word extraction algorithm based on the sum of indegrees comparison, and a minimum context solving algorithm is proposed to construct a dependency grammar tree. Data from 1152 valid papers in the Journal of the China Society for Scientific and Technical Information from 2007 to 2018 was collected for testing, which was compared with the keywords extracted by the classic keyword extraction algorithms TF/IDF, Text-Rank, and LDA. The experimental results show that the context-based dependency grammar analysis algorithm has a positive effect on the extraction of keywords.
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Received: 10 December 2018
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