期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2011
卷号：1
期号：2
页码：46-52
出版社：International Journal of Soft Computing & Engineering
摘要：Social networking websites contain vast amount of data inside them. Volume of data is enormous and growing at a very fast rate. Social network data can be classified in three major categories – user profile data, user communication data and group communication data. Data mining can be applied effectively to discover the knowledge and to extract the useful patterns from this gigantic data set, which is called as the social network mining. Person Related to a Field (PRTF) is a protocol to mine the information across all the social networking data, in general, and use the extracted pattern to search an expert in particular. It also proposes the mechanism to rank the searched experts. In this paper we propose an open source implementation of the PRTF (Person related to a Field) protocol. Using this proposed framework, apart from expert identification, number of useful patterns can be discovered from social networking data. The proposed framework is implemented using open source technologies and is explained with the help of an illustrative example.
关键词：Social network mining; data mining; expert;finding; PRTF.
