Abstract
In this paper we present the first results of detecting word semantic similarity on the Russian translations of Miller-Charles and Rubenstein-Goodenough sets prepared for the first Russian word semantic evaluation Russe-2015. The experiments were carried out on three text collections: Russian Wikipedia, a news collection, and their united collection. We found that the best results in detection of lexical paradigmatic relations are achieved using the combination of word2vec with the new type of features based on word co-occurrences in neighbor sentences.
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CITATION STYLE
Loukachevitch, N., & Alekseev, A. (2016). Gathering information about word similarity from neighbor sentences. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9924 LNCS, pp. 134–141). Springer Verlag. https://doi.org/10.1007/978-3-319-45510-5_16
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