On the nature Of Semantic Similarity and it’S meaSuring with diStributiOnal SemanticS mOdelS
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چکیده
The paper describes our application of the distributional semantic model (DSM) method that we developed for The First International Workshop on Russian Semantic Similarity Evaluation (RUSSE) shared relatedness task. The model was trained, for the most part, on the data of the Russian National Corpus main subcorpus (around 200 mln tokens), and the resulting vector space was weighted according to “ppmi” (Positive Point-wise Mutual Information) and “plmi” (Positive Local Mutual Information) weighting schemes. The results of the workshop show that classical distributional semantic models trained on relatively small corpora can provide data of high quality.
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