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» Mining evolving data streams for frequent patterns
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FSKD
2005
Springer
267views Fuzzy Logic» more  FSKD 2005»
15 years 3 months ago
Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
Discovery of interesting or frequently appearing time series patterns is one of the important tasks in various time series data mining applications. However, recent research critic...
Tak-Chung Fu, Fu-Lai Chung, Robert W. P. Luk, Chak...
SOFTWARE
2002
14 years 9 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
KDD
2012
ACM
164views Data Mining» more  KDD 2012»
13 years 3 days ago
SeqiBloc: mining multi-time spanning blockmodels in dynamic graphs
Blockmodelling is an important technique for decomposing graphs into sets of roles. Vertices playing the same role have similar patterns of interactions with vertices in other rol...
Jeffrey Chan, Wei Liu, Christopher Leckie, James B...
ICDM
2008
IEEE
127views Data Mining» more  ICDM 2008»
15 years 4 months ago
Word Sense Discovery for Web Information Retrieval
Word meaning disambiguation has always been an important problem in many computer science tasks, such as information retrieval and extraction. One of the problems, faced in automa...
Tomasz Nykiel, Henryk Rybinski
CIDM
2009
IEEE
15 years 4 months ago
Mining for insider threats in business transactions and processes
—Protecting and securing sensitive information are critical challenges for businesses. Deliberate and intended actions such as malicious exploitation, theft or destruction of dat...
William Eberle, Lawrence B. Holder