Abstract
It is fundamental and important task to extract keyword form documents. Existing methods mainly use statistical or linguistic information to extract the most salient keyword from document. However, those methods ignore the relationship between different granularities (i.e., relationship between word, sentence, and topic). In order to capture and make better use of their relationships between these granularities, this paper proposed an iterative approach for keyword extraction. The method is first implemented by constructing a graph which reflect relationship between different size of granularity nodes, and then using iterative algorithm to calculate score of keywords. Finally, highest score of words in the document will be chosen as keywords. Experimental results show that our approach outperforms baseline methods.
This paper is funded by College science and technology projects in Shanxi Province china under grant 20110015.
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Wei, Y. (2012). An Iterative Approach to Keywords Extraction. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7332. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31020-1_12
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DOI: https://doi.org/10.1007/978-3-642-31020-1_12
Publisher Name: Springer, Berlin, Heidelberg
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