Abstract
Finding persons who are knowledgeable on a given topic (i.e. Expert Search) has become an active area of recent research [1,2,3] . In this paper we investigate the related task of Intelligent Message Addressing, i.e., finding persons who are potential recipients of a message under composition given its current contents, its previously-specified recipients or a few initial letters of the intended recipient contact (intelligent auto-completion). We begin by providing quantitative evidence, from a very large corpus, of how frequently email users are subject to message addressing problems. We then propose several techniques for this task, including adaptations of well-known formal models of Expert Search. Surprisingly, a simple model based on the K-Nearest-Neighbors algorithm consistently outperformed all other methods. We also investigated combinations of the proposed methods using fusion techniques, which leaded to significant performance improvements over the baselines models. In auto-completion experiments, the proposed models also outperformed all standard baselines. Overall, the proposed techniques showed ranking performance of more than 0.5 in MRR over 5202 queries from 36 different email users, suggesting intelligent message addressing can be a welcome addition to email.
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 (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)
Macdonald, M., Ounis, I.: Voting for candidates: Adapting data fusion techniques for an expert search task. In: CIKM, Arlington, USA, November 6-11 (2006)
Carvalho, V.R., Cohen, W.W.: Predicting recipients in the enron email corpus. Technical Report CMU-LTI-07-005 (2007)
Shetty, J., Adibi, J.: Enron email dataset. Technical report, USC Information Sciences Institute (2004), http://www.isi.edu/~adibi/Enron/Enron.htm
Cohen, W.W.: Enron Email Dataset Webpage, http://www.cs.cmu.edu/~enron/
Joachims, T.: A probabilistic analysis of the rocchio algorithm with TFIDF for text categorization. In: Proceedings of the ICML 1997 (1997)
Salton, G., Buckley, C.: Term weighting approaches in automatic text retrieval. Information Processing and Management 24(5), 513–523 (1988)
Yang, Y., Liu, X.: A re-examination of text categorization methods. In: 22nd Annual International SIGIR, August 1999, pp. 42–49 (1999)
Klimt, B., Yang, Y.: The enron corpus: A new dataset for email classification research. In: Boulicaut, J.-F., Esposito, F., Giannotti, F., Pedreschi, D. (eds.) ECML 2004. LNCS (LNAI), vol. 3201, pp. 217–226. Springer, Heidelberg (2004)
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison-Wesley, Reading (1999)
Aslam, J.A., Montague, M.: Models for metasearch. In: Proceedings of ACM SIGIR, pp. 276–284 (2001)
Ogilvie, P., Callan, J.P.: Combining document representation for known item search. In: ACM SIGIR (2003)
Dom, B., Eiron, I., Cozzi, A., Zhang, Y.: Graph-based ranking algorithms for e-mail expertise analysis. In: Data Mining and Knowledge Discovery Workshop (DMKD2003) in ACM SIGMOD (2003)
Campbell, C.S., Maglio, P.P., Cozzi, A., Dom, B.: Expertise identification using email communications. In: CIKM (2003)
Sihn, W., Heeren, F.: Expert finding within specified subject areas through analysis of e-mail communication. In: Proceedings of the Euromedia 2001 (2001)
Pal, C., McCallum, A.: Cc prediction with graphical models. In: CEAS (2006)
Carvalho, V.R., Cohen, W.W.: Preventing information leaks in email. In: Proceedings of SIAM International Conference on Data Mining (SDM 2007), Minneapolis, MN (2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Carvalho, V.R., Cohen, W.W. (2008). Ranking Users for Intelligent Message Addressing. 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_30
Download citation
DOI: https://doi.org/10.1007/978-3-540-78646-7_30
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)