Adapting Language Modeling Methods for Expert Search to Rank Wikipedia Entities

Authors:
Jiepu Jiang;Wei Lu;Xianqian Rong;Yangyan Gao
Affiliations:
Center for Studies of Information Resources, School of Information Management, Wuhan University, China;Center for Studies of Information Resources, School of Information Management, Wuhan University, China;Center for Studies of Information Resources, School of Information Management, Wuhan University, China;Center for Studies of Information Resources, School of Information Management, Wuhan University, China
Venue:
Advances in Focused Retrieval
Year:
2009

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Abstract

In this paper, we propose two methods to adapt language modeling methods for expert search to the INEX entity ranking task. In our experiments, we notice that language modeling methods for expert search, if directly applied to the INEX entity ranking task, cannot effectively distinguish entity types. Thus, our proposed methods aim at resolving this problem. First, we propose a method to take into account the INEX category query field. Second, we use an interpolation of two language models to rank entities, which can solely work on the text query. Our experiments indicate that both methods can effectively adapt language modeling methods for expert search to the INEX entity ranking task.