With the development of web 2.0, more and more social community applications appeared. The classical type of this kind of application is blog and facebook. The most important feature of these applications is that it i...With the development of web 2.0, more and more social community applications appeared. The classical type of this kind of application is blog and facebook. The most important feature of these applications is that it is a self-media and users can post their own ideas in Internet. By using these social community applications, a big social network is formed. To study the feature of social network, it is important to mine the individual information at the beginning. In this paper, we propose a User Role based method to mine the relation between the user and object thing. First, we extract the User Role from the semantic dictionary Wordnet. Then, the feature of User Role is also mined by considering the hypemymy and hyponymy relation. Finally, we can use these features to deduce the User Role. In our experiments, we use a big corpus from TREC 2006 to test the mining performance. The experiment results show that the User Role effectively explores the feature of user.展开更多
基金National Natural Science Foundations of China (No.60873179, No.60803078)Shenzhen Municipal Science and Technology Planning Program for Basic Research, China ( No. JC200903180630A)+1 种基金Research Fund for the Doctoral Program of Higher Education of China (No.20090121110032)Technology Research Program of Fujian Province of China (No.2006H0037)
文摘With the development of web 2.0, more and more social community applications appeared. The classical type of this kind of application is blog and facebook. The most important feature of these applications is that it is a self-media and users can post their own ideas in Internet. By using these social community applications, a big social network is formed. To study the feature of social network, it is important to mine the individual information at the beginning. In this paper, we propose a User Role based method to mine the relation between the user and object thing. First, we extract the User Role from the semantic dictionary Wordnet. Then, the feature of User Role is also mined by considering the hypemymy and hyponymy relation. Finally, we can use these features to deduce the User Role. In our experiments, we use a big corpus from TREC 2006 to test the mining performance. The experiment results show that the User Role effectively explores the feature of user.
