NASARI: A novel approach to a semantically-aware representation of items

Camacho Collados, Jose ORCID: https://orcid.org/0000-0003-1618-7239, Pilehvar, Mohammad Taher and Navigli, Roberto 2015. NASARI: A novel approach to a semantically-aware representation of items. Presented at: NAACL HLT 2015, Denver, CO, 31 May - 5 June. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. pp. 567-577.

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Abstract

The semantic representation of individual word senses and concepts is of fundamental importance to several applications in Natural Language Processing. To date, concept modeling techniques have in the main based their representation either on lexicographic resources, such as WordNet, or on encyclopedic resources, such as Wikipedia. We propose a vector representation technique that combines the complementary knowledge of both these types of resource. Thanks to its use of explicit semantics combined with a novel cluster-based dimensionality reduction and an effective weighting scheme, our representation attains state-of-the-art performance on multiple datasets in two standard benchmarks: word similarity and sense clustering. We are releasing our vector representations at http://lcl.uniroma1.it/nasari/.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Last Modified:	23 Oct 2022 14:13
URI:	https://orca.cardiff.ac.uk/id/eprint/113080

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