Abstract
One of the major problems for search at Web scale is that the search results on the large scale data might be huge and the users have to browse to find the most relevant ones. Plus, due to the reason for the context, user requirement may diverse although the input query may be the same. In this paper, we try to achieve scalability for Web search through social relation diversity of different users. Namely, we utilize one of the major context for users, social relations, to help refining the search process. Social network based group interest models are developed according to collaborative networks, and is designed to be used in more wider range of Web scale search tasks. The experiments are based on the SwetoDBLP dataset, and we can conclude that proposed method is potentially effective to help users find most relevant search results in the Web environment.
This is a preview of subscription content, log in via an institution to check access.
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
Zeng, Y., Yao, Y.Y., Zhong, N.: Dblp-sse: A dblp search support engine. In: Proceedings of the 2009 IEEE/WIC/ACM International Conference on Web Intelligence, pp. 626–630 (2009)
Aleman-Meza, B., Hakimpour, F., Arpinar, I., Sheth, A.: Swetodblp ontology of computer science publications. Web Semantics: Science, Services and Agents on the World Wide Web 5(3), 151–155 (2007)
Elmacioglu, E., Lee, D.: On six degrees of separation in dblp-db and more. SIGMOD Record 34(2), 33–40 (2005)
Zeng, Y., Wang, Y., Huang, Z., Zhong, N.: Unifying web-scale search and reasoning from the viewpoint of granularity. In: Liu, J., Wu, J., Yao, Y., Nishida, T. (eds.) AMT 2009. LNCS, vol. 5820, pp. 418–429. Springer, Heidelberg (2009)
Balog, K., Azzopardi, L., de Rijke, M.: Formal models for expert finding in enterprise corpora. In: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (2006)
YimamSeid, D., Kobsa, A.: Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach. In: Sharing Expertise: Beyond Knowledge Management, 1st edn., pp. 327–358. The MIT Press, Cambridge (2003)
Zeng, Y., Zhou, E., Qin, Y., Zhong, N.: Research interests: Their dynamics, structures and applications in web search refinement. In: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligenc (2010)
Anderson, J., Schooler, L.: Reflections of the environment in memory. Psychological Science 2(6), 396–408 (1991)
Goldberg, D., Nichols, D., Oki, B.M., Terry, D.: Using collaborative filtering to weave an information tapestry. Communications of the ACM 35(12), 61–70 (1992)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering of netnews. In: Proceedings of the Conference on Computer Supported Cooperative Work, 175–186 (1994)
Bizer, C.: The emerging web of linked data. IEEE Intelligent Systems 24(5), 87–92 (2009)
Cilibrasi, R., Vitanyi, P.M.B.: The google similarity distance. IEEE Transaction on Knowledge and Data Engineering 19(3), 370–383 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ren, X. et al. (2010). Social Relation Based Search Refinement: Let Your Friends Help You!. In: An, A., Lingras, P., Petty, S., Huang, R. (eds) Active Media Technology. AMT 2010. Lecture Notes in Computer Science, vol 6335. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15470-6_48
Download citation
DOI: https://doi.org/10.1007/978-3-642-15470-6_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15469-0
Online ISBN: 978-3-642-15470-6
eBook Packages: Computer ScienceComputer Science (R0)