期刊名称：International Journal of Web & Semantic Technology
印刷版ISSN：0976-2280
电子版ISSN：0975-9026
出版年度：2013
卷号：4
期号：4
DOI：10.5121/ijwest.2013
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Online communities have become vital places for Web 2.0 users to share knowledg e and experiences. Recently, finding expertise user in community has become an important research issue. This paper proposes a novel cascaded model for expert recommendation using aggregated knowledge extracted from enormous contents and social network features. Vector space model is used to compute the relevance of published content with respect to a specific query while PageRank algorithm is applied to rank candidate experts. The experimental results show that the proposed model is an effective recommendation which can guarantee that the most candidate experts are both highly relevant to the specific queries and highly influential in corresponding areas.
关键词：Expert identification; Social network analysis; Information Retrieval; link analysis algorithms
