Abstract
The paper is devoted to the word sense induction problem. We propose a knowledge-poor method, called SenseSearcher (SnS), which induces senses of words from text corpora, based on closed frequent sets. The algorithm discovers a hierarchy of senses, rather than a flat list of concepts, so the results are easier to comprehend. We have evaluated the SnS quality by performing experiments for web search result clustering task with the datasets from SemEval-2013 Task 11.
This work was supported by the National Centre for Research and Development (NCBiR) under Grant No. SP/I/1/77065/10 devoted to the Strategic scientific research and experimental development program: ”Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.
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Kozłowski, M., Rybiński, H. (2014). SnS: A Novel Word Sense Induction Method. In: Kryszkiewicz, M., Cornelis, C., Ciucci, D., Medina-Moreno, J., Motoda, H., Raś, Z.W. (eds) Rough Sets and Intelligent Systems Paradigms. Lecture Notes in Computer Science(), vol 8537. Springer, Cham. https://doi.org/10.1007/978-3-319-08729-0_25
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DOI: https://doi.org/10.1007/978-3-319-08729-0_25
Publisher Name: Springer, Cham
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