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1,393,410
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
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 22 (1 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
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 5 (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 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 23 (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
Words sense disambiguation 2
"... learning algorithm for word sense disambiguation. Word sense disambiguation is concerned with assigning the correct sense to a target word based on the context in which it occurs. The idea behind SenseRelate is that words that occur together in a sentence are semantically related. Quillian [3] intro ..."
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learning algorithm for word sense disambiguation. Word sense disambiguation is concerned with assigning the correct sense to a target word based on the context in which it occurs. The idea behind SenseRelate is that words that occur together in a sentence are semantically related. Quillian [3
Word Sense Disambiguation
"... tion from English to German, needs to translate "bank" as "Ufer" for sense 1a and as "Bank" for sense 1b. An information retrieval system answering a query about "financial banks" should only return documents that use "bank" in sense 1b. Whenever a s ..."
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system's action depends on the meaning of the text being processed, disambiguation is beneficial or even necessary. Although we only cover statistical approaches here, work on word sense disambiguation has a long tradition in Artificial Intelligence and Computational Linguistics. For example, Kelly
Results 1 - 10
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