Sentence to Sentence Similarity

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.

Bounab Yazid, Seppänen Jaakko, Savusalo Markus, Mäkynen Riku, Oussalah Mourad

A4 Article in conference proceedings

Proceedings of the FRUCT’25, Helsinki, Finland, 5-8 November 2019

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

https://fruct.org/publications/acm25 http://urn.fi/urn:nbn:fi-fe202001202596