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» Detecting Change in Data Streams
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CIKM
2010
Springer
13 years 7 months ago
Context modeling for ranking and tagging bursty features in text streams
Bursty features in text streams are very useful in many text mining applications. Most existing studies detect bursty features based purely on term frequency changes without takin...
Wayne Xin Zhao, Jing Jiang, Jing He, Dongdong Shan...
ICAC
2005
IEEE
14 years 2 months ago
Distributed Stream Management using Utility-Driven Self-Adaptive Middleware
We consider pervasive computing applications that process and aggregate data-streams emanating from highly distributed data sources to produce a stream of updates that have an imp...
Vibhore Kumar, Brian F. Cooper, Karsten Schwan
ICMCS
2009
IEEE
114views Multimedia» more  ICMCS 2009»
13 years 6 months ago
Pattern-Push: A low-delay mesh-push scheduling for live peer-to-peer streaming
In live peer-to-peer (P2P) streaming, each peer (child) has a number of supplying parents whose packets have to be scheduled and delivered in time for continuous playback at the c...
Guifeng Zheng, S.-H. Gary Chan, Xiaonan Luo, Ali C...
HICSS
2002
IEEE
90views Biometrics» more  HICSS 2002»
14 years 2 months ago
Knowledge-Based IS Implementation Support: An Application to the IS Change Agent Role Problem
The threat of abandoned or extensively overhauled IS is a major concern for both MIS specialists and businesses. This concern may stem from the mismatch between MIS specialist cha...
Meral Binbasioglu, Elaine Winston
MICCAI
2004
Springer
14 years 10 months ago
A Method to Monitor Local Changes in MR Signal Intensity in Articular Cartilage: A Potential Marker for Cartilage Degeneration i
Osteoarthritis (OA) involves changes in the composition and ultimately the loss of cartilage from articulating joints. MRI has the ability to non-invasively probe the compositional...
Josephine H. Naish, Graham Vincent, Mike Bowes, Ma...