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Authors: Mourad Oussalah and Panos Kostakos

Affiliation: University of Oulu and Centre for Ubiquitous Computing, Finland

Keyword(s): Semantic Similarity, Text Mining, Paraphrasing.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Semantic similarity measures play vital roles in information retrieval, natural language processing and paraphrasing detection. With the growing plagiarisms cases in both commercial and research community, designing efficient tools and approaches for paraphrasing detection becomes crucial. This paper contrasts web-based approach related to analysis of snippets of the search engine with WordNet based measure. Several refinements of the web-based approach will be investigated and compared. Evaluations of the approaches with respect to Microsoft paraphrasing dataset will be performed and discussed.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Oussalah, M. and Kostakos, P. (2017). On Web Based Sentence Similarity for Paraphrasing Detection. In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR; ISBN 978-989-758-271-4; ISSN 2184-3228, SciTePress, pages 289-292. DOI: 10.5220/0006581002890292

@conference{kdir17,
author={Mourad Oussalah. and Panos Kostakos.},
title={On Web Based Sentence Similarity for Paraphrasing Detection},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR},
year={2017},
pages={289-292},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006581002890292},
isbn={978-989-758-271-4},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017) - KDIR
TI - On Web Based Sentence Similarity for Paraphrasing Detection
SN - 978-989-758-271-4
IS - 2184-3228
AU - Oussalah, M.
AU - Kostakos, P.
PY - 2017
SP - 289
EP - 292
DO - 10.5220/0006581002890292
PB - SciTePress