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» Mining data streams: a review
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ICDM
2003
IEEE
240views Data Mining» more  ICDM 2003»
15 years 7 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»
15 years 9 days 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»
16 years 2 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»
16 years 2 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»
13 years 4 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