Results 1 to 10 of about 292 (107)
Word Sense Disambiguation Using Clustered Sense Labels
Applied Sciences (Switzerland), 2022 Sequence labeling models for word sense disambiguation have proven highly effective when the sense vocabulary is compressed based on the thesaurus hierarchy.
Jeong Yeon Park +2 more
exaly +3 more sources
Word sense disambiguation with pictures
Artificial Intelligence, 2005 AbstractWe introduce using images for word sense disambiguation, either alone, or in conjunction with traditional text based methods. The approach is based on a recently developed method for automatically annotating images by using a statistical model for the joint probability for image regions and words. The model itself is learned from a data base of
Kobus Barnard
exaly +2 more sources
Word sense disambiguation of acronyms in clinical narratives
Frontiers in Digital HealthClinical narratives commonly use acronyms without explicitly defining their long forms. This makes it difficult to automatically interpret their sense as acronyms tend to be highly ambiguous.
Pádraig Corcoran +2 more
exaly +3 more sources
Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
doaj +1 more source
Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation
IEEE Access, 2022 The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of ...
Surbhi Bhatia +2 more
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A Method of Word Sense Disambiguation with Recurrent Netural Networks
Journal of Harbin University of Science and Technology, 2020 Word sense disambiguation is an important research problem in natural language processing field. For the phenomenon that a Chinese word has many senses, recurrent neural network (RNN) is used to determine true meaning of ambiguous word with its context ...
ZHANG Chunxiang +2 more
doaj +1 more source
Subjectivity word sense disambiguation [PDF]
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 1 - EMNLP '09, 2009 This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. We provide empirical evidence that SWSD is more feasible than full word sense disambiguation, and that it can be ...
Akkaya, Cem +2 more
openaire +2 more sources
Chinese Word Sense Disambiguation Based on Word translation and Part of speech
Journal of Harbin University of Science and Technology, 2020 For vocabulary ambiguity problem in Chinese, CNN (Convolution Neural Network) is adopted to determine true meaning of ambiguous vocabulary where word, part of speech and translation around its left and right adjacent words are used.
ZHANG Chunxiang +2 more
doaj +1 more source
Word sense disambiguation in queries [PDF]
Proceedings of the 14th ACM international conference on Information and knowledge management, 2005 This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense ...
Shuang Liu, Clement T. Yu, Weiyi Meng
openaire +1 more source
SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation [PDF]
International Journal of Web Research, 2022 Word Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context.
Hossein Rouhizadeh +2 more
doaj +1 more source