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In this paper, we investigate the problem of domain-independent opinion target extraction. The only lexical resource used is domain-independent (general) sentiment dictionary. We begin from investigating syntactic descriptions (rules) using dependency parsing jointly with sentiment dictionary. We conclude that such a solution is not sufficient for opinion target extraction due to low precision. To...
A method for sentiment polarity assignment for textual content written in Polish using supervised machine learning approach with transfer learning scheme is proposed in the paper. It has been shown that performing simple natural language processing steps prior to classification, provides inspiring results without redundant computation overhead. The documents containing subjective opinions were classified...
Word Sense Disambiguation in text is still a difficult problem as the best supervised methods require laborious and costly manual preparation of training data. Thus, this work focuses on evaluation of a few selected clustering algorithms in task of Word Sense Disambiguation for Polish. We tested 6 clustering algorithms (K-Means, K-Medoids, hierarchical agglomerative clustering, hierarchical divisive...
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