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» Evaluating algorithms that learn from data streams
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IPPS
2009
IEEE
16 years 1 months ago
Compact graph representations and parallel connectivity algorithms for massive dynamic network analysis
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Kamesh Madduri, David A. Bader
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
16 years 7 months ago
Turning down the noise in the blogosphere
In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guidin...
Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos...
EUC
2007
Springer
15 years 8 months ago
GPS-Based Location Extraction and Presence Management for Mobile Instant Messenger
Abstract. Location is the most essential presence information for mobile users. In this paper, we present an improved time-based clustering technique for extracting significant lo...
Dexter H. Hu, Cho-Li Wang
COLT
2005
Springer
16 years 1 days ago
From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians
In the machine learning community it is generally believed that graph Laplacians corresponding to a finite sample of data points converge to a continuous Laplace operator if the s...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
16 years 16 days ago
Automatic Construction of N-ary Tree Based Taxonomies
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...
Kunal Punera, Suju Rajan, Joydeep Ghosh