Abstract
We describe a P2P association rule mining descriptor enrichment approach that statistically significantly increases accuracy by greater than 15% over the non-enriched baseline. Unlike the state-of-the-art enrichment approach however, the proposed solution does not introduce additional network load.
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
ipoque, ipoque Internet Study (2008), http://www.ipoque.com/resources/internet_studies
Jia, D., et al.: Distributed, Automatic File Description Tuning in P2P File-Sharing Systems. Peer-to-Peer Networking and Applications 1(2) (September 2008)
Han, J., Kamber, M.: Data Mining: Concepts and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2006)
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
Goharian, N., Frieder, O., Yee, W.G., Mundrawala, J. (2010). Enriching Peer-to-Peer File Descriptors Using Association Rules on Query Logs. In: Gurrin, C., et al. Advances in Information Retrieval. ECIR 2010. Lecture Notes in Computer Science, vol 5993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12275-0_65
Download citation
DOI: https://doi.org/10.1007/978-3-642-12275-0_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-12274-3
Online ISBN: 978-3-642-12275-0
eBook Packages: Computer ScienceComputer Science (R0)