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QED: An Efficient Framework for Temporal Region Query Processing
- Source :
- Advances in Knowledge Discovery and Data Mining ISBN: 9783540260769, PAKDD
- Publication Year :
- 2005
- Publisher :
- Springer Berlin Heidelberg, 2005.
-
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.
Details
- ISBN :
- 978-3-540-26076-9
- ISBNs :
- 9783540260769
- Database :
- OpenAIRE
- Journal :
- Advances in Knowledge Discovery and Data Mining ISBN: 9783540260769, PAKDD
- Accession number :
- edsair.doi...........5fdc20dc1cecbcdb7775dd83978e5b3e