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» Hybrid Learning Scheme for Data Mining Applications
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KDD
2010
ACM
195views Data Mining» more  KDD 2010»
15 years 8 months ago
Universal multi-dimensional scaling
In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is m...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
KDD
2003
ACM
122views Data Mining» more  KDD 2003»
16 years 4 months ago
Understanding captions in biomedical publications
From the standpoint of the automated extraction of scientific knowledge, an important but little-studied part of scientific publications are the figures and accompanying captions....
William W. Cohen, Richard C. Wang, Robert F. Murph...
USENIX
2007
15 years 6 months ago
Load Shedding in Network Monitoring Applications
Monitoring and mining real-time network data streams is crucial for managing and operating data networks. The information that network operators desire to extract from the network...
Pere Barlet-Ros, Gianluca Iannaccone, Josep Sanju&...
EMNLP
2009
15 years 1 months ago
Learning Term-weighting Functions for Similarity Measures
Measuring the similarity between two texts is a fundamental problem in many NLP and IR applications. Among the existing approaches, the cosine measure of the term vectors represen...
Wen-tau Yih
KDD
2004
ACM
158views Data Mining» more  KDD 2004»
16 years 4 months ago
A generalized maximum entropy approach to bregman co-clustering and matrix approximation
Co-clustering is a powerful data mining technique with varied applications such as text clustering, microarray analysis and recommender systems. Recently, an informationtheoretic ...
Arindam Banerjee, Inderjit S. Dhillon, Joydeep Gho...