In this paper, we present a new two-level approach to extract KeyPhrases from textual documents. Our approach relies on a linguistic analysis to extract candidate KeyPhrases and a statistical analysis to rank and filter the final KeyPhrases. We evaluated our approach on three publicly available corpora with documents of varying lengths, domains and languages including English and French. We obtained improvement of Precision, Recall and F-measure. Our results indicate that our approach is independent of the length, the domain and the language.
CITATION STYLE
Ali, C. B., Wang, R., & Haddad, H. (2015). A two-level keyphrase extraction approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9042, pp. 390–401). Springer Verlag. https://doi.org/10.1007/978-3-319-18117-2_29
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