Abstract
Since the introduction of the Enterprise Track at TREC in 2005, the task of finding experts has generated a lot of interest within the research community. Numerous models have been proposed that rank candidates by their level of expertise with respect to some topic. Common to all approaches is a component that estimates the strength of the association between a document and a person. Forming such associations, then, is a key ingredient in expertise search models. In this paper we introduce and compare a number of methods for building document-people associations. Moreover, we make underlying assumptions explicit, and examine two in detail: (i) independence of candidates, and (ii) frequency is an indication of strength. We show that our refined ways of estimating the strength of associations between people and documents leads to significant improvements over the state-of-the-art in the end-to-end expert finding task.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balog, K., Azzopardi, L., de Rijke, M.: Formal models for expert finding in enterprise corpora. In: SIGIR 2006, New York, NY, USA, pp. 43–50 (2006)
Bao, S., Duan, H., Zhou, Q., Xiong, M., Cao, Y., Yu, Y.: Research on Expert Search at Enterprise Track of TREC 2006. In: The Fifteenth Text REtrieval Conference Proceedings (TREC 2006) (2007)
Cao, Y., Liu, J., Bao, S., Li, H.: Research on Expert Search at Enterprise Track of TREC 2005. In: The Fourteenth Text REtrieval Conference Proceedings (TREC 2005) (2006)
Craswell, N., de Vries, A.P., Soboroff, I.: Overview of the TREC-2005 Enterprise Track. In: The Fourteenth Text REtrieval Conference Proceedings (TREC 2005) (2006)
Fang, H., Zhai, C.: Probabilistic Models for Expert Finding. In: Amati, G., Carpineto, C., Romano, G. (eds.) ECIR 2007. LNCS, vol. 4425, pp. 418–430. Springer, Heidelberg (2007)
Fu, Y., Yu, W., Li, Y., Liu, Y., Zhang, M.: THUIR at TREC 2005: Enterprise Track. In: The Fourteenth Text REtrieval Conference Proceedings (TREC 2005) (2006)
Macdonald, C., Ounis, I.: Voting for candidates: adapting data fusion techniques for an expert search task. In: CIKM 2006, pp. 387–396 (2006)
Macdonald, C., Plachouras, V., He, B., Ounis, I.: University of Glasgow at TREC2005: Experiments in Terabyte and Enterprise tracks with Terrier. In: Proceedings of the 14th Text REtrieval Conference (TREC 2005) (2005)
Petkova, D., Croft, W.B.: Hierarchical language models for expert finding in enterprise corpora. In: ICTAI 2006, pp. 599–608 (2006)
Soboroff, I., de Vries, A.P., Craswell, N.: Overview of the TREC 2006 Enterprise Track. In: TREC 2006 Working Notes (2006)
W3C. The W3C test collection (2005), http://research.microsoft.com/users/nickcr/w3c-summary.html
Yimam-Seid, D., Kobsa, A.: Expert finding systems for organizations: Problem and domain analysis and the demoir approach. Journal of Organizational Computing and Electronic Commerce 13(1), 1–24 (2003)
Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to ad hoc information retrieval. In: SIGIR 2001, pp. 334–342 (2001)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Balog, K., de Rijke, M. (2008). Associating People and Documents. In: Macdonald, C., Ounis, I., Plachouras, V., Ruthven, I., White, R.W. (eds) Advances in Information Retrieval. ECIR 2008. Lecture Notes in Computer Science, vol 4956. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78646-7_28
Download citation
DOI: https://doi.org/10.1007/978-3-540-78646-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78645-0
Online ISBN: 978-3-540-78646-7
eBook Packages: Computer ScienceComputer Science (R0)