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» Benchmarking Data Mining Algorithms
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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 6 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
CIKM
1999
Springer
15 years 10 months ago
Requirement-Based Data Cube Schema Design
On-line analytical processing (OLAP) requires e cient processing of complex decision support queries over very large databases. It is well accepted that pre-computed data cubes ca...
David Wai-Lok Cheung, Bo Zhou, Ben Kao, Hongjun Lu...
SIGSOFT
2007
ACM
16 years 7 months ago
Recommending random walks
We improve on previous recommender systems by taking advantage of the layered structure of software. We use a random-walk approach, mimicking the more focused behavior of a develo...
Zachary M. Saul, Vladimir Filkov, Premkumar T. Dev...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
16 years 6 months ago
Co-evolution of social and affiliation networks
In our work, we address the problem of modeling social network generation which explains both link and group formation. Recent studies on social network evolution propose generati...
Elena Zheleva, Hossam Sharara, Lise Getoor
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 6 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...