Information extraction

Lei Zhang, C. Hoede

Research output: Book/ReportReportProfessional

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Abstract

In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that expansion of concepts plays an important role in thinking, so we study the expansion of knowledge graphs to use context information for reasoning and merging of templates.
Original languageUndefined
Place of PublicationEnschede
PublisherUniversity of Twente, Department of Applied Mathematics
Number of pages39
ISBN (Print)0169-2690
Publication statusPublished - 2002

Publication series

NameMemorandum Faculteit TW
PublisherUniversity of Twente, Department of Applied Mathematics
No.1657
ISSN (Print)0169-2690

Keywords

  • MSC-05C99
  • METIS-208514
  • EWI-3477
  • IR-65843
  • MSC-68F99

Cite this

Zhang, L., & Hoede, C. (2002). Information extraction. (Memorandum Faculteit TW; No. 1657). Enschede: University of Twente, Department of Applied Mathematics.