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» Mining data streams: a review
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ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
14 years 2 months ago
Clustering of Time Series Subsequences is Meaningless: Implications for Previous and Future Research
Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences, extracted via a sliding window, has received much attention...
Eamonn J. Keogh, Jessica Lin, Wagner Truppel
SADM
2010
194views more  SADM 2010»
13 years 7 months ago
Seriation and matrix reordering methods: An historical overview
: Seriation is an exploratory combinatorial data analysis technique to reorder objects into a sequence along a one-dimensional continuum so that it best reveals regularity and patt...
Innar Liiv
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
14 years 9 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
KDD
2002
ACM
186views Data Mining» more  KDD 2002»
14 years 9 months ago
Topic-conditioned novelty detection
Automated detection of the first document reporting each new event in temporally-sequenced streams of documents is an open challenge. In this paper we propose a new approach which...
Yiming Yang, Jian Zhang, Jaime G. Carbonell, Chun ...
KDD
2012
ACM
179views Data Mining» more  KDD 2012»
11 years 11 months ago
Web image prediction using multivariate point processes
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
Gunhee Kim, Fei-Fei Li, Eric P. Xing