Abstract
The paper is devoted to solving the task of automatic extraction of keyphrases from a text corpus relating to a specific domain so that the texts linked by common keyphrases would form a well-connected graph. The authors developed a new method that uses a combination of a well-known keyphrase extraction algorithm (e.g., TextRank, Topical PageRank, KEA, Maui) with thesaurus-based procedure that improves the text-via-keyphrase graph connectivity and simultaneously raises the quality of the extracted keyphrases in terms of precision and recall. The effectiveness of the proposed method is demonstrated on the text corpus of the Open Karelia tourist information system.
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The research was supported by the grant of the President of Russian Federation for state support of young Russian scientists (project MK-5456.2016.9).
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Paramonov, I., Lagutina, K., Mamedov, E., Lagutina, N. (2016). Thesaurus-Based Method of Increasing Text-via-Keyphrase Graph Connectivity During Keyphrase Extraction for e-Tourism Applications. In: Ngonga Ngomo, AC., Křemen, P. (eds) Knowledge Engineering and Semantic Web. KESW 2016. Communications in Computer and Information Science, vol 649. Springer, Cham. https://doi.org/10.1007/978-3-319-45880-9_11
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DOI: https://doi.org/10.1007/978-3-319-45880-9_11
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