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Zhang, L. and Hoede, C.
(2002)
Information extraction.
Memorandum 1657,
Department of Applied Mathematics, University of Twente, Enschede.
ISSN 0169-2690
Full text available as: 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.
| Item Type: | Internal Report (Memorandum) |
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| Research Group: | EWI-DMMP: Discrete Mathematics and Mathematical Programming |
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| Additional Information: | Imported from MEMORANDA |
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| ID Code: | 3477 |
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| Deposited On: | 16 July 2006 |
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| Refereed: | No |
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| More Information: | statistics |
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