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| Study on Keyword Extraction Using Word Position Weighted TextRank |
| Xia Tian1,2 |
| Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education, Renmin University of China, Beijing 100872, China) (School of Information Resource Management, Renmin University of China, Beijing 100872, China |
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Abstract The keyword extraction problem is taken as a word importance ranking problem. In this paper,candidate keyword graph is constructed based on TextRank, and the influences of word coverage, location and frequency are used to calculate the probability transition matrix, then, the word score is calculated by iterative method, and the top N candidate keywords are picked as the final results. Experimental results show that the proposed word position weighted TextRank method is better than the traditional TextRank method and LDA topic model method.
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Received: 01 July 2013
Published: 27 September 2013
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