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Content Provider | IEEE Xplore Digital Library |
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Author | Jinghua Wang Jianyi Liu |
Copyright Year | 2005 |
Description | Author affiliation: CISTR, Beijing Univ. of Posts & Telecommun., China (Jinghua Wang; Jianyi Liu) |
Abstract | Learning rules automatically is a hot and difficult topic in information extraction. This paper proposes an algorithm for rule generation in Chinese information extraction - RGA-CIE, which is domain independent for free text of Chinese. RGA-CIE applies supervised learning with bottom-up strategy, which is a rule generalization process with a heuristic method to decide rule generalization path and Laplacian* formula to evaluate the performance of rules. The learned rules have been applied to the experimental system-CHES (comprehensive information based Chinese information extraction system), and achieved good result, which proves the feasibility and effectiveness of RGA-CIE. |
Starting Page | 565 |
Ending Page | 570 |
File Size | 1097923 |
Page Count | 6 |
File Format | |
ISBN | 0780393619 |
DOI | 10.1109/NLPKE.2005.1598801 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2005-10-30 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Laplace equations Information resources Dictionaries Supervised learning Buildings Training data Machine learning Robustness Data mining |
Content Type | Text |
Resource Type | Article |
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