QED: an efficient framework for temporal region query processing

Authors:
Yi-Hong Chu;Kun-Ta Chuang;Ming-Syan Chen
Affiliations:
Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC;Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC;Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, ROC
Venue:
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Year:
2005

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Abstract

In this paper, we explore a new problem of ”temporal dense region query” to discover the dense regions in the constrainted time intervals which can be separated or not. A Querying tEmporal Dense Region framework (abbreviated as QED) proposed to deal with this problem consists of two phases: (1) an offline maintaining phase, to maintain the statistics of data by constructing a number of summarized structures, RF-trees; (2) an online query processing phase, to provide an efficient algorithm to execute queries on the RF-trees. The QED framework has the advantage that by using the summarized structures, RF-trees, the queries can be executed efficiently without accessing the raw data. In addition, a number of RF-trees can be merged with one another efficiently such that the queries will be executed efficiently on the combined RF-tree. As validated by our empirical studies, the QED framework performs very efficiently while producing the results of high quality.