Nearest-neighbor caching for content-match applications Export

@inproceedings{citeulike:5864612, abstract = {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 significantly 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 fitting the actual data to the model.}, address = {New York, NY, USA}, author = {Pandey, Sandeep and Broder, Andrei and Chierichetti, Flavio and Josifovski, Vanja and Kumar, Ravi and Vassilvitskii, Sergei}, booktitle = {WWW '09: Proceedings of the 18th international conference on World wide web}, citeulike-article-id = {5864612}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1526709.1526769}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1526709.1526769}, citeulike-linkout-2 = {http://www2009.org/proceedings/pdf/p441.pdf}, doi = {10.1145/1526709.1526769}, isbn = {978-1-60558-487-4}, keywords = {ads, cache}, location = {Madrid, Spain}, pages = {441--450}, posted-at = {2009-11-08 07:01:10}, priority = {2}, publisher = {ACM}, title = {Nearest-neighbor caching for content-match applications}, url = {http://dx.doi.org/10.1145/1526709.1526769}, year = {2009} }

TY - CONF ID - citeulike:5864612 L3 - citeulike-article-id:5864612 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 significantly 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 fitting the actual data to the model. CY - Madrid, Spain SN - 978-1-60558-487-4 AD - New York, NY, USA EP - 450 TI - Nearest-neighbor caching for content-match applications PB - ACM T2 - WWW '09: Proceedings of the 18th international conference on World wide web SP - 441 KW - ads KW - cache AU - Pandey, Sandeep AU - Broder, Andrei AU - Chierichetti, Flavio AU - Josifovski, Vanja AU - Kumar, Ravi AU - Vassilvitskii, Sergei PY - 2009/// UR - http://dx.doi.org/10.1145/1526709.1526769 ER -