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SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
10 years 6 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
10 years 6 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
SDM
2009
SIAM
394views Data Mining» more  SDM 2009»
10 years 6 months ago
Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence.
Many real-world applications call for learning predictive relationships from multi-modal data. In particular, in multi-media and web applications, given a dataset of images and th...
Oksana Yakhnenko, Vasant Honavar
SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
10 years 6 months ago
Parallel Pairwise Clustering.
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
Elad Yom-Tov, Noam Slonim
SDM
2009
SIAM
129views Data Mining» more  SDM 2009»
10 years 6 months ago
Scalable Distributed Change Detection from Astronomy Data Streams Using Local, Asynchronous Eigen Monitoring Algorithms.
This paper considers the problem of change detection using local distributed eigen monitoring algorithms for next generation of astronomy petascale data pipelines such as the Larg...
Kamalika Das, Kanishka Bhaduri, Sugandha Arora, We...
SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
10 years 6 months ago
Detecting Communities in Social Networks Using Max-Min Modularity.
Many datasets can be described in the form of graphs or networks where nodes in the graph represent entities and edges represent relationships between pairs of entities. A common ...
Jiyang Chen, Osmar R. Zaïane, Randy Goebel
SDM
2009
SIAM
130views Data Mining» more  SDM 2009»
10 years 6 months ago
Grammar Mining.
We introduce the problem of grammar mining, where patterns are context-free grammars, as a generalization of a large number of common pattern mining tasks, such as tree, sequence ...
Luc De Raedt, Siegfried Nijssen
SDM
2009
SIAM
170views Data Mining» more  SDM 2009»
10 years 6 months ago
Mining Complex Spatio-Temporal Sequence Patterns.
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often...
Florian Verhein
SDM
2009
SIAM
108views Data Mining» more  SDM 2009»
10 years 6 months ago
Highlighting Diverse Concepts in Documents.
We show the underpinnings of a method for summarizing documents: it ingests a document and automatically highlights a small set of sentences that are expected to cover the differ...
Evimaria Terzi, Kun Liu, Tyrone Grandison
SDM
2009
SIAM
184views Data Mining» more  SDM 2009»
10 years 6 months ago
DensEst: Density Estimation for Data Mining in High Dimensional Spaces.
Subspace clustering and frequent itemset mining via “stepby-step” algorithms that search the subspace/pattern lattice in a top-down or bottom-up fashion do not scale to large ...
Emmanuel Müller, Ira Assent, Ralph Krieger, S...
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