Search results for "Sentence Similarity"

showing 2 items of 2 documents

Semantic Word Error Rate for Sentence Similarity

2016

Sentence similarity measures have applications in several tasks, including: Machine Translation, Paraphrase Iden- tification, Speech Recognition, Question-answering and Text Summarization. However, measures designed for these tasks are aimed at assessing equivalence rather than resemblance, partly departing from human cognition of similarity. While this is reasonable for these activities, it hinders the applicability of sentence similarity measures to other tasks. We therefore propose a new sentence similarity measure specifically designed for resemblance evaluation, in order to cover these fields better. Experimental results are discussed.

Machine translationComputer scienceSpeech recognitionWord error rate02 engineering and technologycomputer.software_genreParaphrase030507 speech-language pathology & audiology03 medical and health sciencesSemantic similarityArtificial IntelligenceLSAWord Error Rate0202 electrical engineering electronic engineering information engineeringsentence resemblanceEquivalence (formal languages)Latent Semantic AnalysiSemantic Word Error Ratesentence similarity measureSWERbusiness.industryLatent semantic analysisSentence SimilaritySemantic ComputingCognitionAutomatic summarizationComputer Networks and Communicationword relatedne020201 artificial intelligence & image processingArtificial intelligence0305 other medical sciencebusinesscomputerNatural language processingWERInformation Systems2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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An Innovative Similarity Measure for Sentence Plagiarism Detection

2016

We propose and experimentally assess Semantic Word Error Rate (SWER), an innovative similarity measure for sentence plagiarism detection. SWER introduces a complex approach based on latent semantic analysis, which is capable of outperforming the accuracy of competitor methods in plagiarism detection. We provide principles and functionalities of SWER, and we complement our analytical contribution by means of a significant preliminary experimental analysis. Derived results are promising, and confirm to use the goodness of our proposal.

business.industryComputer scienceLatent semantic analysisPlagiarism DetectionComputer Science (all)Sentence similarity measureWord error rate02 engineering and technologySimilarity measurecomputer.software_genreComplement (complexity)Theoretical Computer SciencePlagiarism detection020204 information systems0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingPlagiarism detectionArtificial intelligenceSentence Similarity MeasurebusinesscomputerNatural language processingSentencePlagiarism detection; Sentence similarity measure; Theoretical Computer Science; Computer Science (all)
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