Summarizing multidimensional data streams: a hierarchy-graph-based approach

Authors:
Yoann Pitarch;Anne Laurent;Pascal Poncelet
Affiliations:
LIRMM - Univ Montpellier 2, CNRS, Montpellier, France;LIRMM - Univ Montpellier 2, CNRS, Montpellier, France;LIRMM - Univ Montpellier 2, CNRS, Montpellier, France
Venue:
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Year:
2010

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Abstract

When dealing with potentially infinite data streams, storing the whole data stream history is unfeasible and providing a high-quality summary is required In this paper, we propose a summarization method for multidimensional data streams based on a graph structure and taking advantage of the data hierarchies The summarization method considers the data distribution and thus overcomes a major drawback of the Tilted Time Window common framework We adapt this structure for synthesizing frequent itemsets extracted on temporal windows Thanks to our approach, as users do not analyze any more numerous extraction results, the result processing is improved.