Rumen Moraliyski

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We describe a new unsupervised approach for synonymy discovery by aligning paraphrases in monolingual domain corpora. For that purpose, we identify phrasal terms that convey most of the concepts within domains and adapt a methodology for the automatic extraction and alignment of paraphrases to identify paraphrase casts from which valid synonyms are(More)
Thesauri, that list the most salient semantic relations between words have mostly been compiled manually. Therefore, the inclusion of an entry depends on the subjective decision of the lexicographer. As a consequence, those resources are usually incomplete. In this paper, we propose an unsupervised methodology to automatically discover pairs of semantically(More)
This paper describes the HULTECH team participation in Task 3 of SemEval-2014. Four different subtasks are provided to the participants , who are asked to determine the semantic similarity of cross-level test pairs: paragraph-to-sentence, sentence-to-phrase, phrase-to-word and word-to-sense. Our system adopts a unified strategy (general purpose system) to(More)
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