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PAMI
2008
161views more  PAMI 2008»
13 years 7 months ago
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models
The Expectation Maximization (EM) algorithm is widely used for learning finite mixture models despite its greedy nature. Most popular model-based clustering techniques might yield...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
ICDM
2005
IEEE
189views Data Mining» more  ICDM 2005»
14 years 1 months ago
Integrating Hidden Markov Models and Spectral Analysis for Sensory Time Series Clustering
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Jie Yin, Qiang Yang
JCP
2006
111views more  JCP 2006»
13 years 7 months ago
Mining Developing Trends of Dynamic Spatiotemporal Data Streams
This paper1 presents an efficient modeling technique for data streams in a dynamic spatiotemporal environment and its suitability for mining developing trends. The streaming data a...
Yu Meng, Margaret H. Dunham
KDD
2004
ACM
136views Data Mining» more  KDD 2004»
14 years 7 months ago
A cross-collection mixture model for comparative text mining
In this paper, we define and study a novel text mining problem, which we refer to as Comparative Text Mining (CTM). Given a set of comparable text collections, the task of compara...
ChengXiang Zhai, Atulya Velivelli, Bei Yu
CORR
2008
Springer
99views Education» more  CORR 2008»
13 years 7 months ago
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an associatio...
Michael Hahsler