Affix modification-based bilingual pivoting method for paraphrase extraction in agglutinative languages

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dc.contributor.authorPark, Hancheolko
dc.contributor.authorGweon, Gahgeneko
dc.contributor.authorHeo, Jeongko
dc.date.accessioned2023-09-25T06:00:48Z-
dc.date.available2023-09-25T06:00:48Z-
dc.date.created2023-09-25-
dc.date.issued2016-01-
dc.identifier.citationInternational Conference on Big Data and Smart Computing, BigComp 2016, pp.199 - 206-
dc.identifier.issn2375-933X-
dc.identifier.urihttp://hdl.handle.net/10203/312910-
dc.description.abstractParaphrase extraction is a task that involves the extraction of pairs of paraphrase expressions from a large-scale corpus. Because existing extraction methods are mostly designed for morphologically poor languages such as English, we present a method suited for agglutinative languages that are morphologically complex by attaching inflectional affixes to word stems. Specifically, we use the Korean language as a case study to address two types of problems that occur because existing methods model each lexical form as a separate word. The first problem is lexical data sparsity, and the second problem is not considering the morphological word structure. To mitigate these problems, we propose a novel phrasal paraphrase extraction method called affix modification-based bilingual pivoting method (AMBPM), which extends the existing bilingual pivoting method (BPM). Our experiments show that our proposed method significantly outperforms two state-of-the-art paraphrase extraction methods, namely the syntactic constraints-based bilingual pivoting method (SCBPM) and the skip-gram word embedding model with respect to meaning preservation and grammaticality of the extracted paraphrase pairs.-
dc.languageEnglish-
dc.publisherInstitute of Electrical and Electronics Engineers Inc.-
dc.titleAffix modification-based bilingual pivoting method for paraphrase extraction in agglutinative languages-
dc.typeConference-
dc.identifier.wosid000381792400028-
dc.identifier.scopusid2-s2.0-84964689158-
dc.type.rimsCONF-
dc.citation.beginningpage199-
dc.citation.endingpage206-
dc.citation.publicationnameInternational Conference on Big Data and Smart Computing, BigComp 2016-
dc.identifier.conferencecountryCC-
dc.identifier.conferencelocationHong Kong-
dc.identifier.doi10.1109/BIGCOMP.2016.7425914-
dc.contributor.localauthorGweon, Gahgene-
dc.contributor.nonIdAuthorHeo, Jeong-
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IE-Conference Papers(학술회의논문)
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