University of Oulu

Bounab, Y., Seppänen, J., Savusalo, M., Mäkynen, R., Oussalah, M., Sentence to sentence similarity : a review, Proceedings of the FRUCT’25, Helsinki, Finland, 5-8 November 2019, ISSN: 2305-7254, p. 439-443

Sentence to sentence similarity : a review

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Author: Bounab, Yazid1; Seppänen, Jaakko1; Savusalo, Markus1;
Organizations: 1University of Oulu, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202001202596
Language: English
Published: FRUCT, 2019
Publish Date: 2020-01-20
Description:

Abstract

This paper suggests a novel sentence-to-sentence similarity measure. The proposal makes use of both word embedding and named-entity based semantic similarity. This is motivated by the increasing short text phrases that contain named-entity tags and the importance to detect various levels of hidden semantic similarity even in case of high noise ratio. The proposal is evaluated using a set of publicly available datasets as well as an in-house built dataset, while comparison with some state of art algorithms is performed.

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Series: Proceedings of Conference of Open Innovations Association FRUCT
ISSN: 2305-7254
ISSN-E: 2343-0737
ISSN-L: 2305-7254
ISBN: 978-952-69244-0-3
Pages: 439 - 443
Host publication: Proceedings of the FRUCT’25, Helsinki, Finland, 5-8 November 2019
Host publication editor: Balandin, S.
Niemi, V.
Tuytina, T.
Conference: Conference of Open Innovations Association FRUCT
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Funding: This work is partly supported by CBC Karelia IoT Business Creation (2018-2020) and EU YoungRes (#823701) projects.
Copyright information: © The Authors 2019.