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» Warping the time on data streams
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COCOON
2005
Springer
14 years 1 months ago
Finding Longest Increasing and Common Subsequences in Streaming Data
In this paper, we present algorithms and lower bounds for the Longest Increasing Subsequence (LIS) and Longest Common Subsequence (LCS) problems in the data streaming model. For t...
David Liben-Nowell, Erik Vee, An Zhu
ICDM
2009
IEEE
167views Data Mining» more  ICDM 2009»
13 years 5 months ago
Self-Adaptive Anytime Stream Clustering
Clustering streaming data requires algorithms which are capable of updating clustering results for the incoming data. As data is constantly arriving, time for processing is limited...
Philipp Kranen, Ira Assent, Corinna Baldauf, Thoma...
SIGMOD
2007
ACM
108views Database» more  SIGMOD 2007»
14 years 7 months ago
Travel time estimation using NiagaraST and latte
To address increasing traffic congestion and its associated consequences, traffic managers are turning to intelligent transportation management. The latte project is extending dat...
Kristin Tufte, Jin Li, David Maier, Vassilis Papad...
SSDBM
2005
IEEE
111views Database» more  SSDBM 2005»
14 years 1 months ago
Querying Streaming Geospatial Image Data: The GeoStreams Project
Data products generated from remotely-sensed, geospatial imagery (RSI) used in emerging areas, such as global climatology, environmental monitoring, land use, and disaster managem...
Quinn Hart, Michael Gertz
AMW
2010
13 years 9 months ago
Robust Clustering of Data Streams using Incremental Optimization
Discovering the patterns in evolving data streams is a very important and challenging task. In many applications, it is useful to detect the dierent patterns evolving over time and...
Basheer Hawwash, Olfa Nasraoui