Combining and learning word embedding with WordNet for semantic relatedness and similarity measurement
Author:
Affiliation:
1. National Taiwan University Taipei City Taiwan
2. National Chengchi University Taipei City Taiwan
3. MOST Joint Research Center for AI Technology and All Vista Healthcare Taiwan
Publisher
Wiley
Subject
Library and Information Sciences,Information Systems and Management,Computer Networks and Communications,Information Systems
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/asi.24289
Reference49 articles.
1. Agirre E. Alfonseca E. Hall K. Kravalova J. Paşca M. &Soroa A.(2009).A study on similarity and relatedness using distributional and wordnet‐based approaches. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics 19–27. Denver CO: Association for Computational Linguistics.
2. Lemon and Tea Are Not Similar: Measuring Word-to-Word Similarity by Combining Different Methods
3. 10.1162/153244303322533223
4. Multimodal Distributional Semantics
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