Word Sense Detection (WSD) Algorithm

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A word sense detection (WSD) algorithm is a multi-class shallow semantic NLP algorithm that can be implemented by a WSD system to solve a WSD task.



References

2020

2019

  • (Hadiwinoto et al., 2019) ⇒ Christian Hadiwinoto, Hwee Tou Ng, and Wee Chung Gan. (2019). “Improved Word Sense Disambiguation Using Pre-trained Contextualized Word Representations.” In: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).

2009

  • (Sinha & Mihalcea, 2009) ⇒ Ravi Sinha, and Rada Mihalcea. (2009). “Unsupervised Graph-based Word Sense Disambiguation.” In: “Current Issues in Linguistic Theory: Recent Advances in Natural Language Processing”, Editors Nicolas Nicolov and Ruslan Mitkov. John Benjamins Publishers. ISBN:1556195915

2007

2006a

2006b

  • (AgirreMLS) ⇒ Eneko Agirre, David Martínez, Oier López de Lacalle and Aitor Soroa. (2006). “Two graph-based algorithms for state-of-the-art WSD.” In: Proceedings of EMNLP06 at ACL06.
    • This paper explores the use of two graph algorithms for unsupervised induction and tagging of nominal word senses based on corpora.

2005

2004

2003a

2003b

2002

1998a

1998b

  • (Leacock & Chodorow, 1998) ⇒ Claudia Leacock, and Martin Chodorow. (1998). “Combining local context with WordNet Similarity for Word Sense Identification].” In: Christiane Fellbaum, editor, WordNet: A Lexical Reference System and its Application. MIT Press, Cambridge, MA.

1998c

1997

  • (Jiang and Conrath) ⇒ Jay J. Jiang, and David W. Conrath. (1997). “Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy.” In: Proceedings on International Conference on Research in Computational Linguistics.

1996a

1996b

1995

1993

1986