TY  - CONF
ID  - www200945
UR  - http://www2009.eprints.org/45/
A1  - Pandey, Sandeep
A1  - Broder, Andrei
A1  - Chierichetti, Flavio
A1  - Josifovski, Vanja
A1  - Kumar, Ravi
A1  - Vassilvitskii, Sergei
Y1  - 2009/04//
N2  - Motivated by contextual advertising systems and other web applications involving efficiency?accuracy tradeoffs, we study similarity caching. Here, a cache hit is said to occur if the requested item is similar but not necessarily equal to some cached item. We study two objectives that dictate the efficiency?accuracy tradeoff and provide our caching policies for these objectives. By conducting extensive experiments on real data we show similarity caching can signi?cantly improve the efficiency of contextual advertising systems, with minimal impact on accuracy. Inspired by the above, we propose a simple generative model that embodies two fundamental characteristics of page requests arriving to advertising systems, namely, long-range dependences and similarities. We provide theoretical bounds on the gains of similarity caching in this model and demonstrate these gains empirically by ?tting the actual data to the model.
TI  - Nearest-Neighbor Caching for Content-Match Applications
SP  - 441
M2  - Madrid, Spain
AV  - public
EP  - 441
T2  - 18th International World Wide Web Conference
ER  -