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ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
14 years 1 months ago
Belief Propagation in Large, Highly Connected Graphs for 3D Part-Based Object Recognition
We describe a part-based object-recognition framework, specialized to mining complex 3D objects from detailed 3D images. Objects are modeled as a collection of parts together with...
Frank DiMaio, Jude W. Shavlik
ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
14 years 1 months ago
Mining for Tree-Query Associations in a Graph
New applications of data mining, such as in biology, bioinformatics, or sociology, are faced with large datasets structured as graphs. We present an efficient algorithm for minin...
Eveline Hoekx, Jan Van den Bussche
ICDM
2006
IEEE
109views Data Mining» more  ICDM 2006»
14 years 1 months ago
Star-Structured High-Order Heterogeneous Data Co-clustering Based on Consistent Information Theory
Heterogeneous object co-clustering has become an important research topic in data mining. In early years of this research, people mainly worked on two types of heterogeneous data ...
Bin Gao, Tie-Yan Liu, Wei-Ying Ma
ICDM
2006
IEEE
102views Data Mining» more  ICDM 2006»
14 years 1 months ago
Who Thinks Who Knows Who? Socio-cognitive Analysis of Email Networks
Interpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be ...
Nishith Pathak, Sandeep Mane, Jaideep Srivastava
ICDM
2006
IEEE
131views Data Mining» more  ICDM 2006»
14 years 1 months ago
Intelligent Icons: Integrating Lite-Weight Data Mining and Visualization into GUI Operating Systems
The vast majority of visualization tools introduced so far are specialized pieces of software that are explicitly run on a particular dataset at a particular time for a particular...
Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Stefano Lona...
ICDM
2006
IEEE
149views Data Mining» more  ICDM 2006»
14 years 1 months ago
Pattern Mining in Frequent Dynamic Subgraphs
Graph-structured data is becoming increasingly abundant in many application domains. Graph mining aims at finding interesting patterns within this data that represent novel knowl...
Karsten M. Borgwardt, Hans-Peter Kriegel, Peter Wa...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
14 years 1 months ago
Adding Semantics to Email Clustering
This paper presents a novel algorithm to cluster emails according to their contents and the sentence styles of their subject lines. In our algorithm, natural language processing t...
Hua Li, Dou Shen, Benyu Zhang, Zheng Chen, Qiang Y...
ICDM
2006
IEEE
133views Data Mining» more  ICDM 2006»
14 years 1 months ago
An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph, namely the exponential diffusion kernel, the Laplacian diffusion kernel, the ...
François Fouss, Luh Yen, Alain Pirotte, Mar...
ICDM
2006
IEEE
100views Data Mining» more  ICDM 2006»
14 years 1 months ago
Meta Clustering
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
14 years 1 months ago
Adaptive Blocking: Learning to Scale Up Record Linkage
Many information integration tasks require computing similarity between pairs of objects. Pairwise similarity computations are particularly important in record linkage systems, as...
Mikhail Bilenko, Beena Kamath, Raymond J. Mooney