Abstract
Existing desktop search applications, trying to keep up with the rapidly increasing storage capacities of our hard disks, are an important step towards more efficient personal information management, yet they offer an incomplete solution. While their indexing functionalities in terms of different file types they are able to cope with are impressive, their ranking capabilities are basic, and rely only on textual retrieval measures, comparable to the first generation of web search engines. In this paper we propose to connect semantically related desktop items by exploiting usage analysis information about sequences of accesses to local resources, as well as about each user’s local resource organization structures. We investigate and evaluate in detail the possibilities to translate this information into a desktop linkage structure, and we propose several algorithms that exploit these newly created links in order to efficiently rank desktop items. Finally, we empirically show that the access based links lead to ranking results comparable with TFxIDF ranking, and significantly surpass TFxIDF when used in combination with it, making them a very valuable source of input to desktop search ranking algorithms.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Adar, E., Kargar, D., Stein, L.A.: Haystack: per-user information environments. In: Proc. of the 8th Intl. CIKM Conf. on Information and Knowledge Management (1999)
Baeza-Yates, R.A., Ribeiro-Neto, B.A.: Modern Information Retrieval. ACM Press, New York (1999)
Chirita, P.A., Gavriloaie, R., Ghita, S., Nejdl, W., Paiu, R.: Activity based metadata for semantic desktop search. In: Proc. of the 2nd European Semantic Web Conference (2005)
Chirita, P.-A., Costache, S., Nejdl, W., Paiu, R.: Beagle + + : Semantically enhanced searching and ranking on the desktop. In: Sure, Y., Domingue, J. (eds.) ESWC 2006. LNCS, vol. 4011, pp. 348–362. Springer, Heidelberg (2006)
Claypool, M., Brown, D., Le, P., Waseda, M.: Inferring user interest. IEEE Internet Computing 5(6) (2001)
Dumais, S., Cutrell, E., Cadiz, J., Jancke, G., Sarin, R., Robbins, D.: Stuff i’ve seen: a system for personal information retrieval and re-use. In: Proc. of the 26th Intl. ACM SIGIR Conf. on Research and Development in Informaion Retrieval, pp. 72–79 (2003)
Gemmell, J., Bell, G., Lueder, R., Drucker, S., Wong, C.: Mylifebits: fulfilling the memex vision. In: Proc. of the ACM Conference on Multimedia (2002)
Jones, K.S., Walker, S., Robertson, S.: Probabilistic model of information retrieval: Development and status. Technical report, Cambridge University (1998)
Karger, D.R., Bakshi, K., Huynh, D., Quan, D., Sinha, V.: Haystack: A customizable general-purpose information management tool for end users of semistructured data. In: Proc. of the 1st Intl. Conf. on Innovative Data Syst. (2003)
Kendall, M.: Rank Correlation Methods. Hafner Publishing (1955)
Oard, D., Kim, J.: Modeling information content using observable behavior. In: Proceedings of the 64th Annual Meeting of the American Society for Information Science and Technology (2001)
Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Technical report, Stanford University (1998)
Quan, D., Karger, D.: How to make a semantic web browser. In: Proc. of the 13th Intl. WWW Conf. (2004)
Soules, C., Ganger, G.: Connections: using context to enhance file search. In: SOSP (2005)
Teevan, J., Dumais, S.T., Horvitz, E.: Personalizing search via automated analysis of interests and activities. In: Proc. of the 28th Intl. ACM SIGIR Conf. on Research and Development in Information Retrieval (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chirita, PA., Nejdl, W. (2006). Analyzing User Behavior to Rank Desktop Items. In: Crestani, F., Ferragina, P., Sanderson, M. (eds) String Processing and Information Retrieval. SPIRE 2006. Lecture Notes in Computer Science, vol 4209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880561_8
Download citation
DOI: https://doi.org/10.1007/11880561_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45774-9
Online ISBN: 978-3-540-45775-6
eBook Packages: Computer ScienceComputer Science (R0)