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An improved self-learning model based social relationship extraction.

Author(s)
Chongwen Wang School of Software, Beijing Institute of Technology, 100081, Beijing, China
Tong Shen School of Software, Beijing Institute of Technology, 100081, Beijing, China
Yi Huang School of Software, Beijing Institute of Technology, 100081, Beijing, China
Abstract
How to extract social relations from the text content in internet is a problem. A supervised method based on machine learning algorithm has been used to solve the problem. Based on the characteristics of social relationship, the appropriate rules have been made for feature extraction. Based on the result of feature extraction, two methods have been proposed which are support vector machine (SVM) and the maximum entropy model for the relation extraction experiment. The results show that support vector machine algorithm is better than the maximum entropy model.
Publication Details
Page(s) 713-718
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 46, Issue: 2, Year: 2012

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