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Author:

He, Ming (He, Ming.) | Du, Yong-Ping (Du, Yong-Ping.) (Scholars:杜永萍) | Yan, Shi-Rui (Yan, Shi-Rui.)

Indexed by:

EI Scopus

Abstract:

Information extraction (IE) is the problem of constructing a knowledge base from a corpus of text documents. In recent years, uncertain data applications have grown in importance in the large number of real-world applications, and IE as an uncertain data source. This paper investigated the uncertain data represent and presented a probabilistic framework from IE model that adapting principles of a state-of-the-art statistical model-semi-Conditional Random Fields (semi-CRFs), which provides a sound probability distribution over extractions.

Keyword:

Knowledge based systems Random processes Artificial intelligence Data mining Probability distributions Information retrieval Software engineering

Author Community:

  • [ 1 ] [He, Ming]College of Computer Science, Beijing University of Technology, Beijing, China
  • [ 2 ] [Du, Yong-Ping]College of Computer Science, Beijing University of Technology, Beijing, China
  • [ 3 ] [Yan, Shi-Rui]College of Computer Science, Beijing University of Technology, Beijing, China

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Source :

Year: 2010

Page: 390-392

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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