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KDD
2009
ACM
132views Data Mining» more  KDD 2009»
14 years 10 months ago
Learning patterns in the dynamics of biological networks
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
KDD
2009
ACM
198views Data Mining» more  KDD 2009»
14 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...
KDD
2009
ACM
229views Data Mining» more  KDD 2009»
14 years 10 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
KDD
2009
ACM
296views Data Mining» more  KDD 2009»
14 years 10 months ago
Anonymizing healthcare data: a case study on the blood transfusion service
: Gaining access to high-quality health data is a vital requirement to informed decision making for medical practitioners and pharmaceutical researchers. Driven by mutual benefits ...
Noman Mohammed, Benjamin C. M. Fung, Patrick C. K....
KDD
2009
ACM
140views Data Mining» more  KDD 2009»
14 years 10 months ago
Improving clustering stability with combinatorial MRFs
: ? Improving Clustering Stability with Combinatorial MRFs Bekkerman, Ron; Scholz, Martin; Viswanathan, Krishnamurthy HP Laboratories HPL-2009-46 Clustering stability, combinatoria...
Ron Bekkerman, Martin Scholz, Krishnamurthy Viswan...
KDD
2009
ACM
203views Data Mining» more  KDD 2009»
14 years 10 months ago
Characterizing individual communication patterns
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 10 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
KDD
2009
ACM
169views Data Mining» more  KDD 2009»
14 years 10 months ago
COA: finding novel patents through text analysis
In recent years, the number of patents filed by the business enterprises in the technology industry are growing rapidly, thus providing unprecedented opportunities for knowledge d...
Mohammad Al Hasan, W. Scott Spangler, Thomas D. Gr...
KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 10 months ago
The offset tree for learning with partial labels
We present an algorithm, called the offset tree, for learning in situations where a loss associated with different decisions is not known, but was randomly probed. The algorithm i...
Alina Beygelzimer, John Langford
KDD
2009
ACM
216views Data Mining» more  KDD 2009»
14 years 10 months ago
Finding a team of experts in social networks
Given a task T , a pool of individuals X with different skills, and a social network G that captures the compatibility among these individuals, we study the problem of finding X ,...
Theodoros Lappas, Kun Liu, Evimaria Terzi