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.
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Jiang, J., Lu, W., Rong, X., Gao, Y. (2009). Adapting Language Modeling Methods for Expert Search to Rank Wikipedia Entities. In: Geva, S., Kamps, J., Trotman, A. (eds) Advances in Focused Retrieval. INEX 2008. Lecture Notes in Computer Science, vol 5631. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03761-0_27
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DOI: https://doi.org/10.1007/978-3-642-03761-0_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03760-3
Online ISBN: 978-3-642-03761-0
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