Using Soft-Matching Mined Rules to Improve Information Extraction
作者： Un Yong Nahm , Raymond J. Mooney
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摘要: By discovering predictive relationships between different pieces of extracted data, data-mining algorithms can be used to improve the accuracy information extraction. However, textual variation due typos, abbreviations, and other sources prevent productive discovery utilization hard-matching rules. Recent methods for inducing softmatching rules from data more effectively find exploit in data. This paper presents techniques using mined soft-matching association increase Experimental results on a corpus computer-science job postings demonstrate that extraction than
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