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» Mining time-changing data streams
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VLDB
2010
ACM
144views Database» more  VLDB 2010»
13 years 6 months ago
Methods for finding frequent items in data streams
The frequent items problem is to process a stream of items and find all items occurring more than a given fraction of the time. It is one of the most heavily studied problems in d...
Graham Cormode, Marios Hadjieleftheriou
SDM
2007
SIAM
106views Data Mining» more  SDM 2007»
13 years 9 months ago
Performance of Recommendation Systems in Dynamic Streaming Environments
In this paper, we study the behavior of collaborative filtering based recommendations under evolving user profile scenarios. We propose a systematic validation methodology that ...
Olfa Nasraoui, Jeff Cerwinske, Carlos Rojas, Fabio...
CORR
2000
Springer
230views Education» more  CORR 2000»
13 years 7 months ago
Integrating E-Commerce and Data Mining: Architecture and Challenges
We show that the e-commerce domain can provide all the right ingredients for successful data mining. We describe an integrated architecture for supporting this integration. The ar...
Suhail Ansari, Ron Kohavi, Llew Mason, Zijian Zhen...
PAKDD
2010
ACM
189views Data Mining» more  PAKDD 2010»
14 years 10 days ago
Subsequence Matching of Stream Synopses under the Time Warping Distance
In this paper, we propose a method for online subsequence matching between histogram-based stream synopsis structures under the dynamic warping distance. Given a query synopsis pat...
Su-Chen Lin, Mi-Yen Yeh, Ming-Syan Chen
CORR
2008
Springer
113views Education» more  CORR 2008»
13 years 7 months ago
Document stream clustering: experimenting an incremental algorithm and AR-based tools for highlighting dynamic trends
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Alain Lelu, Martine Cadot, Pascal Cuxac