Abstract
How well can the relevance of a page be predicted, purely based on snippets? This would be highly useful in a Federated Web Search setting where caching large amounts of result snippets is more feasible than caching entire pages. The experiments reported in this paper make use of result snippets and pages from a diverse set of actual Web search engines. A linear classifier is trained to predict the snippet-based user estimate of page relevance, but also, to predict the actual page relevance, again based on snippets alone. The presented results confirm the validity of the proposed approach and provide promising insights into future result merging strategies for a Federated Web Search setting.
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.
Similar content being viewed by others
References
Arguello, J., Callan, J., Diaz, F.: Classification-based resource selection. In: CIKM 2009. ACM Press, New York (2009)
Clarke, C.L.A., Craswell, N., Soboroff, I., Cormack, G.V.: Overview of the TREC 2010 Web Track. In: TREC, pp. 1–9 (2010)
Demeester, T., Nguyen, D., Trieschnigg, D., Develder, C., Hiemstra, D.: What Snippets Say about Pages in Federated Web Search. In: Hou, Y., Nie, J.-Y., Sun, L., Wang, B., Zhang, P. (eds.) AIRS 2012. LNCS, vol. 7675, pp. 250–261. Springer, Heidelberg (2012)
Nguyen, D., Demeester, T., Trieschnigg, D., Hiemstra, D.: Federated Search in the Wild: the Combined Power of over a Hundred Search Engines. In: CIKM 2012 (2012)
Nigam, K., Lafferty, J., Mccallum, A.: Using Maximum Entropy for Text Classification. In: IJCAI 1999 Workshop on Information Filtering (1999)
Shokouhi, M., Li, L.: Federated Search. Foundations and Trends in Information Retrieval 5(1), 1–102 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Demeester, T., Nguyen, D., Trieschnigg, D., Develder, C., Hiemstra, D. (2013). Snippet-Based Relevance Predictions for Federated Web Search. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_63
Download citation
DOI: https://doi.org/10.1007/978-3-642-36973-5_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36972-8
Online ISBN: 978-3-642-36973-5
eBook Packages: Computer ScienceComputer Science (R0)