Results 71 to 80 of about 83,914 (327)
Improving Data Integration through Disambiguation Techniques [PDF]
, 2008 In this paper Word Sense Disambiguation (WSD) issue in the context of data integration is outlined and an Approximate Word Sense Disambiguation approach (AWSD) is proposed for the automatic lexical annotation of structured and semi-structured data ...
PO, Laura
core +2 more sources
Annual Meeting of the Association for Computational Linguistics, 2021 Lately proposed Word Sense Disambiguation (WSD) systems have approached the estimated upper bound of the task on standard evaluation benchmarks. However, these systems typically implement the disambiguation of words in a document almost independently ...
Ming Wang, Yinglin Wang
semanticscholar +1 more source
Interpretability in Word Sense Disambiguation using Tsetlin Machine
International Conference on Agents and Artificial Intelligence, 2021 : Word Sense Disambiguation (WSD) is a longstanding unresolved task in Natural Language Processing. The challenge lies in the fact that words with the same spelling can have completely different senses, sometimes depending on subtle characteristics of ...
Rohan Kumar Yadav +3 more
semanticscholar +1 more source
Adapting BERT for Word Sense Disambiguation with Gloss Selection Objective and Example Sentences [PDF]
Findings, 2020 Domain adaptation or transfer learning using pre-trained language models such as BERT has proven to be an effective approach for many natural language processing tasks.
Boon Peng Yap +2 more
semanticscholar +1 more source
Word sense disambiguation and information retrieval [PDF]
, 1994 It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval (IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will increase.
Sanderson, M.
core +1 more source
Word vs. Class-Based Word Sense Disambiguation [PDF]
, 2015 As empirically demonstrated by the Word Sense Disambiguation (WSD) tasks of the last SensEval/SemEval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed.
Izquierdo Beviá, Rubén +2 more
core +2 more sources
Memory-Based Word Sense Disambiguation
Computers and the Humanities, 2000 We describe a memory-based classification architecture for word sense disambiguation and its application to the SENSEVAL evaluation task. For each ambiguous word, a semantic word expert is automatically trained using a memory-based approach. In each expert, selecting the correct sense of a word in a new context is achieved by finding the closest match ...
Veenstra, J. +4 more
openaire +6 more sources
Attention Neural Network for Biomedical Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2022 In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang +4 more
doaj +1 more source
Evaluation of Linguistic Features for Word Sense Disambiguation with Self-Organized Document Maps [PDF]
, 2004 Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense ...
Linden, Krister
core +1 more source
SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation
AAAI Conference on Artificial Intelligence, 2020 Contextual representations of words derived by neural language models have proven to effectively encode the subtle distinctions that might occur between different meanings of the same word.
Bianca Scarlini +2 more
semanticscholar +1 more source