Results 31 to 40 of about 29,475 (177)
Subjectivity word sense disambiguation [PDF]
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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Improving Data Integration through Disambiguation Techniques [PDF]
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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Word sense disambiguation using Conceptual Density [PDF]
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-sense disambiguation using decomposable models [PDF]
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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WORD SENSE DISAMBIGUATION FOR TAMIL LANGUAGE USING PART-OF-SPEECH AND CLUSTERING TECHNIQUE [PDF]
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
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
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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Word domain disambiguation via word sense disambiguation [PDF]
Word subject domains have been widely used to improve the performance of word sense disambiguation algorithms. However, comparatively little effort has been devoted so far to the disambiguation of word subject domains. The few existing approaches have focused on the development of algorithms specific to word domain disambiguation.
Sanfilippo, Antonio P. +2 more
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Word vs. Class-Based Word Sense Disambiguation [PDF]
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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Determining the difficulty of Word Sense Disambiguation [PDF]
Automatic processing of biomedical documents is made difficult by the fact that many of the terms they contain are ambiguous. Word Sense Disambiguation (WSD) systems attempt to resolve these ambiguities and identify the correct meaning. However, the published literature on WSD systems for biomedical documents report considerable differences in ...
McInnes, Bridget T., Stevenson, Mark
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