Chunk Parsing and Entity Relation Extracting to Chinese Text by Using Conditional Random Fields Model

Wu, Junhua and Liu, Longxia (2010) Chunk Parsing and Entity Relation Extracting to Chinese Text by Using Conditional Random Fields Model. Journal of Intelligent Learning Systems and Applications, 02 (03). pp. 139-146. ISSN 2150-8402

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Abstract

Currently, large amounts of information exist in Web sites and various digital media. Most of them are in natural lan-guage. They are easy to be browsed, but difficult to be understood by computer. Chunk parsing and entity relation extracting is important work to understanding information semantic in natural language processing. Chunk analysis is a shallow parsing method, and entity relation extraction is used in establishing relationship between entities. Because full syntax parsing is complexity in Chinese text understanding, many researchers is more interesting in chunk analysis and relation extraction. Conditional random fields (CRFs) model is the valid probabilistic model to segment and label sequence data. This paper models chunk and entity relation problems in Chinese text. By transforming them into label solution we can use CRFs to realize the chunk analysis and entities relation extraction.

Item Type: Article
Subjects: Souths Book > Engineering
Depositing User: Unnamed user with email support@southsbook.com
Date Deposited: 27 Jan 2023 08:08
Last Modified: 24 Jun 2024 05:31
URI: http://research.europeanlibrarypress.com/id/eprint/118

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