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STOC
2004
ACM
145views Algorithms» more  STOC 2004»
16 years 7 months ago
Using mixture models for collaborative filtering
A collaborative filtering system at an e-commerce site or similar service uses data about aggregate user behavior to make recommendations tailored to specific user interests. We d...
Jon M. Kleinberg, Mark Sandler
SIGMOD
2009
ACM
171views Database» more  SIGMOD 2009»
16 years 7 months ago
GAMPS: compressing multi sensor data by grouping and amplitude scaling
We consider the problem of collectively approximating a set of sensor signals using the least amount of space so that any individual signal can be efficiently reconstructed within...
Sorabh Gandhi, Suman Nath, Subhash Suri, Jie Liu
SIGMOD
2009
ACM
190views Database» more  SIGMOD 2009»
16 years 7 months ago
DataLens: making a good first impression
When a database query has a large number of results, the user can only be shown one page of results at a time. One popular approach is to rank results such that the "best&quo...
Bin Liu, H. V. Jagadish
SIGMOD
2006
ACM
232views Database» more  SIGMOD 2006»
16 years 7 months ago
To search or to crawl?: towards a query optimizer for text-centric tasks
Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive...
Panagiotis G. Ipeirotis, Eugene Agichtein, Pranay ...
PODS
2005
ACM
151views Database» more  PODS 2005»
16 years 7 months ago
Estimating arbitrary subset sums with few probes
Suppose we have a large table T of items i, each with a weight wi, e.g., people and their salary. In a general preprocessing step for estimating arbitrary subset sums, we assign e...
Noga Alon, Nick G. Duffield, Carsten Lund, Mikkel ...
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