A parallel system for text inference using marker propagations
This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution...
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| Veröffentlicht in: | IEEE transactions on parallel and distributed systems Jg. 9; H. 8; S. 729 - 747 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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IEEE
01.08.1998
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| ISSN: | 1045-9219 |
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| Abstract | This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the basis for the development of a large linguistic knowledge base. The inference algorithm consists of a set of highly parallel search methods that, when applied to the knowledge base, find contexts in which sentences are interpreted. These contexts reveal information relevant to the text. Implementation, results, and parallelism analysis are discussed. |
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| AbstractList | This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the basis for the development of a large linguistic knowledge base. The inference algorithm consists of a set of highly parallel search methods that, when applied to the knowledge base, find contexts in which sentences are interpreted. These contexts reveal information relevant to the text. Implementation, results, and parallelism analysis are discussed. This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to natural language applications such as information extraction and dissemination, text understanding, summarization, and translation. Our solution takes advantage of a semantic English dictionary available in electronic form that provides the basis for the development of a large linguistic knowledge base. The inference algorithm consists of a set of highly parallel search methods that, when applied to the knowledge base, find contexts in which sentences are interpreted. These contexts reveal information relevant to the text. Implementation, results, and parallelism analysis are discussed |
| Author | Moldovan, D.I. Harabagiu, S.M. |
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| References | mcroy (bibl072919) 1992; 18 marcus (bibl072916) 1993; 19 quillian (bibl072922) 1966 ratnaparkhi (bibl072923) 1996 hendler (bibl072914) 1988 charniak (bibl07297) 1989 bibl072915 bibl07292 bibl072912 bibl072918 bibl07295 bibl07293 bibl072917 bibl07294 tou ng (bibl072920) 1996 bibl072921 gupta (bibl072911) 1987 wilks (bibl072928) 1996 harabagiu (bibl072913) 1997 wilensky (bibl072927) 1983 schank (bibl072924) 1986 bibl072925 bibl072926 bibl072929 alterman (bibl07291) 1989 fillmore (bibl072910) 1968 yu (bibl072930) 1990 cohen (bibl07298) 1988 fahlman (bibl07299) 1979 charniak (bibl07296) 1986 |
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| Snippet | This paper presents a possible solution for the text inference problem-extracting information unstated in a text, but implied. Text inference is central to... This paper presents a possible solution for the text inference problem - extracting information unstated in a text, but implied. Text inference is central to... |
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| SubjectTerms | Computer science Computer Society Data mining Humans Inference algorithms Information retrieval Natural language processing Natural languages Parallel processing Text recognition |
| Title | A parallel system for text inference using marker propagations |
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