Abstract
During the past decade, information retrieval techniques have been augmented in order to search for experts and not just documents. This is done by searching document collections for both query topics and associated experts. A typical approach assumes that expert candidates are authors of intranet documents, or that they engage in social writing activities on blogs or online forums. However, in many organizations, the actual experts, i.e., the people who work on problems in their day-to-day work, rarely engage in such writing activities. As an alternative, we turn to structured corporate data—transactions of working hours provided by an organization’s ERP system—as a source of evidence for ranking experts. We design an expert finding system for such an enterprise and conclude that it is possible to utilize such transactional data, which is a result of required daily business processes, to provide a solid source of evidence for expert finding.
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References
Amitay, E., Carmel, D., Golbandi, N., Har’El, N., Ofek-Koifman, S., Yogev, S.: Finding people and documents, using web 2.0 data. In: Proceedings of SIGIR Workshop: Future Challenges in Expertise Retrieval, pp. 1–5 (2008)
Balog, K.: The sigir 2008 workshop on future challenges in expertise retrieval (fcher). SIGIR Forum 42(2), 46–52 (2008)
Balog, K., Azzopardi, L., de Rijke, M.: Formal models for expert finding in enterprise corpora. In: Proceedings of ACM SIGIR, pp. 43–50 (2006)
Balog, K., de Rijke, M.: Non-local evidence for expert finding. In: Proceedings of CIKM, pp. 489–498 (2008)
Craswell, N., de Vries, A., Soboroff, I.: Overview of the trec 2005 enterprise track. In: The 14th Text REtrieval Conference Proceedings, TREC 2005 (2006)
Craswell, N., Hawking, D., Vercoustre, A.-M., Wilkins, P.: P@noptic expert: Searching for experts not just for documents. In: Poster Proceedings of AusWeb (2001)
Davenport, T., Prusak, L.: Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press, Boston (1998)
Kolari, P., Finn, T., Lyons, K., Yesha, Y.: Expert search using internal corporate blogs. In: Proceedings of SIGIR Workshop: Future Challenges in Expertise Retrieval, pp. 7–10 (2008)
Petkova, D., Croft, W.B.: Hierarchical language models for expert finding in enterprise corpora. In: Proceedings of ICTAI, pp. 599–608 (2006)
Ponte, J., Croft, W.: A language modeling approach to information retrieval. In: Proceedings of ACM SIGIR, pp. 275–281 (1998)
Silberschatz, A., Korth, H., Sudarshan, S.: Database System Concepts, 5th edn. McGraw-Hill, New York (2006)
Zhai, C., Lafferty, J.: A study of smoothing methods for language models applied to ad hoc information retrieval. In: Proceedings of ACM SIGIR, pp. 334–342 (2001)
Zhou, Y., Cong, G., Cui, B., Jensen, C., Yao, J.: Routing questions to the right users in online communities. In: Proceedings of ICDE, pp. 700–711 (2009)
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Schunk, L.K., Cong, G. (2010). Using Transactional Data from ERP Systems for Expert Finding. In: Bringas, P.G., Hameurlain, A., Quirchmayr, G. (eds) Database and Expert Systems Applications. DEXA 2010. Lecture Notes in Computer Science, vol 6262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15251-1_22
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DOI: https://doi.org/10.1007/978-3-642-15251-1_22
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