Unsupervised keyphrase extraction: Introducing new kinds of words to keyphrases

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Abstract

Current studies often extract keyphrases by collecting adjacent important adjectives and nouns. However, the statistics on four public corpora shows that about 15% of keyphrases contain other kinds of words. Even so, incorporating such kinds of words to the noun phrase patterns is not a solution to improve the extraction performance. In this work, we propose a solution to improve the extraction performance by involving new kinds of words to keyphrases. We have experimented on four public corpora to demonstrate that our proposal improve the performance of keyphrase extraction and new kinds of words are introduced to keyphrases. In addition, our proposal is also superior to the current unsupervised keyphrase extraction approaches.

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Le, T. T. N., Nguyen, M. L., & Shimazu, A. (2016). Unsupervised keyphrase extraction: Introducing new kinds of words to keyphrases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9992 LNAI, pp. 665–671). Springer Verlag. https://doi.org/10.1007/978-3-319-50127-7_58

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