Results 31 to 40 of about 29,481 (177)
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
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Using Linked Disambiguated Distributional Networks for Word Sense Disambiguation [PDF]
Proceedings of the 1st Workshop on Sense, Concept and Entity
Representations and their Applications, 2017 We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on a resource that links two types of sense-aware lexical networks: one is induced from a corpus using distributional semantics, the other is manually constructed.
Alexander Panchenko +3 more
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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 ...
Cem Akkaya, Janyce Wiebe, Rada Mihalcea
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WORD SENSE DISAMBIGUATION FOR TAMIL LANGUAGE USING PART-OF-SPEECH AND CLUSTERING TECHNIQUE [PDF]
Journal of Engineering Science and Technology, 2017 Word sense disambiguation is an important task in Natural Language Processing (NLP), and this paper concentrates on the problem of target word selection in machine translation.
P. ISWARYA, V. RADHA
doaj
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
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A Corpus-Based Word Sense Disambiguation For Geez Language
Ethiopian Journal of Science and Sustainable Development, 2021 In natural language processing, languages have a number of ambiguous words and solving such kind of problem for the language can help the development of word sense disambiguation using corpusbased Approach.
Amlakie Aschale Alemu, Kinde Anlay Fante
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Biomedical Word Sense Disambiguation with Word Embeddings [PDF]
, 2017 There is a growing need for automatic extraction of information and knowledge from the increasing amount of biomedical and clinical data produced, namely in textual form. Natural language processing comes in this direction, helping in tasks such as information extraction and information retrieval.
Antunes, Rui, Matos, Sérgio
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Word sense disambiguation using Conceptual Density [PDF]
Proceedings of the 16th conference on Computational linguistics -, 1996 This paper presents a method for the resolution of lexical ambiguity of nouns and its automatic evaluation over the Brown Corpus. The method relies on the use of the wide-coverage noun taxonomy of WordNet and the notion of conceptual distance among concepts, captured by a Conceptual Density formula developed for this purpose.
Agirre, Eneko, Rigau, German
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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
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Word-sense disambiguation using decomposable models [PDF]
Proceedings of the 32nd annual meeting on Association for Computational Linguistics -, 1994 Most probabilistic classifiers used for word-sense disambiguation have either been based on only one contextual feature or have used a model that is simply assumed to characterize the interdependencies among multiple contextual features. In this paper, a different approach to formulating a probabilistic model is presented along with a case study of the
Bruce, Rebecca, Wiebe, Janyce
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