AAAI Publications, Workshops at the Thirtieth AAAI Conference on Artificial Intelligence

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Coupled Semi-Supervised Learning for Chinese Knowledge Extraction
Leeheng Ma, Yi-Ting Tsao, Yen-Ling Kuo, Jane Yung-jen Hsu

Last modified: 2016-03-29


Robust intelligent systems may leverage knowledge about the world to cope with a variety of contexts.While automatic knowledge extraction algorithms have been successfully used to build knowledge bases in English,little progress has been made in extracting non-alphabetic languages, e.g. Chinese.This paper identifies the key challenge in instance and pattern extraction for Chinese and presents the Coupled Chinese Pattern Learner that utilizes part-of-speech tagging and language-dependent grammar rules for generalized matching in the Chinese never-ending language learner framework for large-scale knowledge extraction from online documents.Experiments showed that the proposed system is scalable and achieves a precision of 79.9% in learning categories after a small number of iterations.


Semi-supervised learning; Bootstrap learning; Knowledge extraction; Information Extraction; Web mining

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