@inproceedings{fe9a93fd4dae41efb3515036d244aa7d,
title = "QED: An efficient framework for temporal region query processing",
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.",
author = "Chu, {Yi Hong} and Chuang, {Kun Ta} and Chen, {Ming Syan}",
year = "2005",
doi = "10.1007/11430919_39",
language = "English",
isbn = "3540260765",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "323--332",
booktitle = "Advances in Knowledge Discovery and Data Mining - 9th Pacific-Asia Conference, PAKDD 2005, Proceedings",
address = "Germany",
note = "9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005 ; Conference date: 18-05-2005 Through 20-05-2005",
}