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KDD
2009
ACM
198views Data Mining» more  KDD 2009»
15 years 10 months ago
Pervasive parallelism in data mining: dataflow solution to co-clustering large and sparse Netflix data
All Netflix Prize algorithms proposed so far are prohibitively costly for large-scale production systems. In this paper, we describe an efficient dataflow implementation of a coll...
Srivatsava Daruru, Nena M. Marin, Matt Walker, Joy...
WWW
2010
ACM
15 years 4 months ago
Equip tourists with knowledge mined from travelogues
With the prosperity of tourism and Web 2.0 technologies, more and more people have willingness to share their travel experiences on the Web (e.g., weblogs, forums, or Web 2.0 comm...
Qiang Hao, Rui Cai, Changhu Wang, Rong Xiao, Jiang...
VLDB
2001
ACM
139views Database» more  VLDB 2001»
15 years 1 months ago
NetCube: A Scalable Tool for Fast Data Mining and Compression
We propose an novel method of computing and storing DataCubes. Our idea is to use Bayesian Networks, which can generate approximate counts for any query combination of attribute v...
Dimitris Margaritis, Christos Faloutsos, Sebastian...
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KDD
2008
ACM
115views Data Mining» more  KDD 2008»
15 years 10 months ago
Topical query decomposition
We introduce the problem of query decomposition, where we are given a query and a document retrieval system, and we want to produce a small set of queries whose union of resulting...
Francesco Bonchi, Carlos Castillo, Debora Donato, ...
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
15 years 10 months ago
The "DGX" distribution for mining massive, skewed data
Skewed distributions appear very often in practice. Unfortunately, the traditional Zipf distribution often fails to model them well. In this paper, we propose a new probability di...
Zhiqiang Bi, Christos Faloutsos, Flip Korn