Research on Personal Education Background Extraction Using Rules

Z.M. Zhong, C. H. Li

Abstract


With the explosive growth of Internet information, how to obtain the required information from the vast amounts of text information is becoming an important issue today. Extraction of personal attribute has made considerable progress, including name, sex, place of birth, date of birth, related events, etc. But the extraction of personal education background information does not arouse researcher?s enough attention. The attribute of personal education background is very complex in text and involves all kinds of education structures such as primary school, middle school and university. We put forward a new method of extracting personal attributes from texts based on rules. Firstly, rules of personal education background are formulated after analyzing a lot of texts about people. Secondly, the related algorithm is designed to extract personal education background from unstructured texts based on rules. Finally, the experiment is implemented for 100 documents about people. The results show that the average precision of extracting personal education background is 0.898, the average recall is 0.8959, and the average F-measure is 0.8968.

Keywords


personal attribute extraction; personal education background extraction; personal education background rules

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Copyright (c) 2017 Z.M. Zhong, C. H. Li


International Journal of Emerging Technologies in Learning. ISSN: 1863-0383
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