Affiliation:
1. Università di Roma La Sapienza, Rome, Italy
Abstract
Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.
Publisher
Association for Computing Machinery (ACM)
Subject
General Computer Science,Theoretical Computer Science
Cited by
830 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Enhancing Word Sense Disambiguation for Amharic homophone words using Bidirectional Long Short-Term Memory network;Intelligent Systems with Applications;2024-09
2. Density Matrices for Metaphor Understanding;Electronic Proceedings in Theoretical Computer Science;2024-08-12
3. GC-PCWR+ for Word Sense Disambiguation;2024 International Conference on Asian Language Processing (IALP);2024-08-04
4. Leveraging Bilingual Dictionaries for Improved Setswana-English Machine Translation: A Context-Aware Model;2024 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD);2024-08-01
5. Sino-Vietnamese Text Transcription using Word Embedding Approach;2024 Tenth International Conference on Communications and Electronics (ICCE);2024-07-31