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From Lexical to Semantic Features in Paraphrase Identification
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Fialho, Pedro; Quaresma, Paulo. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2019. : OASIcs - OpenAccess Series in Informatics. 8th Symposium on Languages, Applications and Technologies (SLATE 2019), 2019
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Abstract:
The task of paraphrase identification has been applied to diverse scenarios in Natural Language Processing, such as Machine Translation, summarization, or plagiarism detection. In this paper we present a comparative study on the performance of lexical, syntactic and semantic features in the task of paraphrase identification in the Microsoft Research Paraphrase Corpus. In our experiments, semantic features do not represent a gain in results, and syntactic features lead to the best results, but only if combined with lexical features.
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Keyword:
Data processing Computer science; lexical features; paraphrase identification; semantic features; syntactic features
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URN:
urn:nbn:de:0030-drops-108763
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URL: https://doi.org/10.4230/OASIcs.SLATE.2019.9 https://drops.dagstuhl.de/opus/volltexte/2019/10876/
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Paraphrase Plagiarism Identifcation with Character-level Features
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Semantically-informed distance and similarity measures for paraphrase plagiarism identification
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Vietnamese Sentence Similarity Based on Concepts
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In: Lecture Notes in Computer Science ; 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM) ; https://hal.inria.fr/hal-01405592 ; 13th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Nov 2014, Ho Chi Minh City, Vietnam. pp.243-253, ⟨10.1007/978-3-662-45237-0_24⟩ (2014)
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A Paraphrase-Based Approach to Machine Translation Evaluation
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In: DTIC (2005)
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On Paraphrase Identification Corpora
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In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1000_Paper.pdf
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