Sciweavers

93 search results - page 5 / 19
» Extracting k most important groups from data efficiently
Sort
View
PAMI
2006
127views more  PAMI 2006»
14 years 9 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
PVLDB
2010
252views more  PVLDB 2010»
14 years 4 months ago
Efficient and Effective Similarity Search over Probabilistic Data based on Earth Mover's Distance
Probabilistic data is coming as a new deluge along with the technical advances on geographical tracking, multimedia processing, sensor network and RFID. While similarity search is...
Jia Xu, Zhenjie Zhang, Anthony K. H. Tung, Ge Yu
ICDE
2009
IEEE
131views Database» more  ICDE 2009»
15 years 11 months ago
Exploring a Few Good Tuples from Text Databases
Information extraction from text databases is a useful paradigm to populate relational tables and unlock the considerable value hidden in plain-text documents. However, information...
Alpa Jain, Divesh Srivastava
81
Voted
SDM
2009
SIAM
205views Data Mining» more  SDM 2009»
15 years 6 months ago
Identifying Information-Rich Subspace Trends in High-Dimensional Data.
Identifying information-rich subsets in high-dimensional spaces and representing them as order revealing patterns (or trends) is an important and challenging research problem in m...
Chandan K. Reddy, Snehal Pokharkar
EAAI
2010
91views more  EAAI 2010»
14 years 9 months ago
A framework for on-line trend extraction and fault diagnosis
: Qualitative trend analysis (QTA) is a process-history-based data-driven technique that works by extracting important features (trends) from the measured signals and evaluating th...
Mano Ram Maurya, Praveen K. Paritosh, Raghunathan ...