Abstract
We present Serelex, a system that provides, given a query in English, a list of semantically related words. The terms are ranked according to an original semantic similarity measure learnt from a huge corpus. The system performs comparably to dictionary-based baselines, but does not require any semantic resource such as WordNet. Our study shows that users are completely satisfied with 70% of the query results. © 2013 Springer-Verlag.
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CITATION STYLE
Panchenko, A., Romanov, P., Morozova, O., Naets, H., Philippovich, A., Romanov, A., & Fairon, C. (2013). Serelex: Search and visualization of semantically related words. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7814 LNCS, pp. 837–840). https://doi.org/10.1007/978-3-642-36973-5_97
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