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11,139
Subjectivity Word Sense Disambiguation
"... 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 ..."
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Cited by 27 (2 self)
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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
Analogical Word Sense Disambiguation
"... Word sense disambiguation is an important problem in learning by reading. This paper introduces analogical word-sense disambiguation, which uses human-like analogical processing over structured, relational representations to perform word sense disambiguation. Cases are automatically constructed usin ..."
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Word sense disambiguation is an important problem in learning by reading. This paper introduces analogical word-sense disambiguation, which uses human-like analogical processing over structured, relational representations to perform word sense disambiguation. Cases are automatically constructed
Soft Word Sense Disambiguation
"... Abstract: Word sense disambiguation is a core problem in many tasks related to language processing. In this paper, we introduce the notion of soft word sense disambiguation which states that given a word, the sense disambiguation system should not commit to a particular sense, but rather, to a set o ..."
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Abstract: Word sense disambiguation is a core problem in many tasks related to language processing. In this paper, we introduce the notion of soft word sense disambiguation which states that given a word, the sense disambiguation system should not commit to a particular sense, but rather, to a set
Soft Word Sense Disambiguation
- Masaryk University Brno, Brno, Czech Republic
, 2004
"... Word sense disambiguation is a core problem in many tasks related to language processing. In this paper, we introduce the notion of soft word sense disambiguation which states that given a word, the sense disambiguation system should not commit to a particular sense, but rather, to a set of sense ..."
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Cited by 7 (0 self)
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Word sense disambiguation is a core problem in many tasks related to language processing. In this paper, we introduce the notion of soft word sense disambiguation which states that given a word, the sense disambiguation system should not commit to a particular sense, but rather, to a set
Dutch Word Sense Disambiguation:
"... We describe a new version of the Dutch word sense disambiguation system trained and tested on a corrected version of the SENSEVAL-2 data. The system is an ensemble of word experts; each word expert is a memory-based classifier of which the parameters are automatically determined through cross ..."
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Cited by 2 (0 self)
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We describe a new version of the Dutch word sense disambiguation system trained and tested on a corrected version of the SENSEVAL-2 data. The system is an ensemble of word experts; each word expert is a memory-based classifier of which the parameters are automatically determined through
Word Sense Disambiguation
"... ABSTRACT: Ambiguity and human language have been tangled since the rise of philological communication. One of the long established problems of Natural Language Processing (NLP) is Word Sense Disambiguation (WSD). Researchers have been diligently trying to deal with this problem since the birth of M ..."
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ABSTRACT: Ambiguity and human language have been tangled since the rise of philological communication. One of the long established problems of Natural Language Processing (NLP) is Word Sense Disambiguation (WSD). Researchers have been diligently trying to deal with this problem since the birth
Word sense disambiguation in queries
- In ACM Conference on Information and Knowledge Management (CIKM2005
, 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 hyp ..."
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Cited by 24 (0 self)
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and hyponyms, and its domains, can be used for word sense disambiguation. By comparing these pieces of information associated with the words which form a phrase, it may be possible to assign senses to these words. If the above disambiguation fails, then other query words, if exist, are used, by going through
Smoothing and Word Sense Disambiguation
- IN PROCEEDINGS OF ESTAL - ESPAÑA FOR NATURAL LANGUAGE PROCESSING
, 2004
"... This paper presents an algorithm to apply the smoothing techniques described in [1] to three different Machine Learning (ML) methods for Word Sense Disambiguation (WSD). The method to obtain better estimations for the features is explained step by step, and applied to n-way ambiguities. The results ..."
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Cited by 4 (3 self)
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This paper presents an algorithm to apply the smoothing techniques described in [1] to three different Machine Learning (ML) methods for Word Sense Disambiguation (WSD). The method to obtain better estimations for the features is explained step by step, and applied to n-way ambiguities. The results
Word Sense Disambiguation with . . .
- NATURAL LANGUAGE ENGINEERING, SPECIAL ISSUE ON WORD SENSE DISAMBIGUATION SYSTEMS
, 2002
"... This paper presents a novel approach for word sense disambiguation. The underlying algorithm has two main components: (1) pattern learning from available sense-tagged corpora (SemCor), from dictionary de nitions (WordNet) and from a generated corpus (GenCor), and (2) instance based learning with au ..."
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This paper presents a novel approach for word sense disambiguation. The underlying algorithm has two main components: (1) pattern learning from available sense-tagged corpora (SemCor), from dictionary de nitions (WordNet) and from a generated corpus (GenCor), and (2) instance based learning
Word sense disambiguation: a survey
- ACM COMPUTING SURVEYS
, 2009
"... 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 ..."
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Cited by 191 (16 self)
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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
Results 1 - 10
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11,139
