tailieunhanh - Báo cáo khoa học: "A Probabilistic Model for Fine-Grained Expert Search"

Expert search, in which given a query a ranked list of experts instead of documents is returned, has been intensively studied recently due to its importance in facilitating the needs of both information access and knowledge discovery. Many approaches have been proposed, including metadata extraction, expert profile building, and formal model generation. However, all of them conduct expert search with a coarse-grained approach. With these, further improvements on expert search are hard to achieve. . | A Probabilistic Model for Fine-Grained Expert Search Shenghua Bao1 Huizhong Duan1 Qi Zhou1 Miao Xiong1 Yunbo Cao1 2 Yong Yu1 Shanghai Jiao Tong University 2Microsoft Research Asia Shanghai China 200240 Beijing China 100080 shhbao summer jackson xiongmiao yyu @ Abstract Expert search in which given a query a ranked list of experts instead of documents is returned has been intensively studied recently due to its importance in facilitating the needs of both information access and knowledge discovery. Many approaches have been proposed including metadata extraction expert profile building and formal model generation. However all of them conduct expert search with a coarse-grained approach. With these further improvements on expert search are hard to achieve. In this paper we propose conducting expert search with a fine-grained approach. Specifically we utilize more specific evidences existing in the documents. An evidence-oriented probabilistic model for expert search and a method for the implementation are proposed. Experimental results show that the proposed model and the implementation are highly effective. 1 Introduction Nowadays team work plays a more important role than ever in problem solving. For instance within an enterprise people handle new problems usually by leveraging the knowledge of experienced colleagues. Similarly within research communities novices step into a new research area often by learning from well-established researchers in the research area. All these scenarios involve asking the questions like who is an expert on X or who knows about X Such questions which cannot be answered easily through traditional document search raise a new requirement of searching people with certain expertise. To meet that requirement a new task called expert search has been proposed and studied intensively. For example TREC 2005 2006 and 2007 provide the task of expert search within the enterprise track. In the TREC setting .