This paper addresses the problem of timestamped event sequence matching, a new type of sequence matching that retrieves the occurrences of interesting patterns from a timestamped event sequence. Timestamped event sequence matching is useful for discovering temporal causal relationships among timestamped events. In this paper, we first point out the shortcomings of prior approaches to this problem and then propose a novel method that employs an R*-tree to overcome them. To build an R*-tree, it places a time window at every position of a times-tamped event sequence and represents each window as an n-dimensional rectangle by considering the first and last occurrence times of each event type. Here, n is the total number of disparate event types that may occur in a target application. When n is large, we apply a grouping technique to reduce the dimensionality of an R*-tree. To retrieve the occurrences of a query pattern from a timestamped event sequence, the proposed method first identifies a small number of candidates by searching an R*-tree and then picks out true answers from them. We prove its robustness formally, and also show its effectiveness via extensive experiments.
|Number of pages||10|
|Journal||Lecture Notes in Computer Science|
|Publication status||Published - 2005|
|Event||16th International Conference on Database and Expert Systems Applications, DExa 2005 - Copenhagen, Denmark|
Duration: 2005 Aug 22 → 2005 Aug 26
Bibliographical noteFunding Information:
★ This work was partially supported by Korea Research Foundation Grant funded by Korea Government (MOEHRD, Basic Research Promotion Fund) (KRF-2005-206-D00015), by the ITRC support program(MSRC) of IITA, and by the research fund of Korea Research Foundation with Grant KRF-2003-041-D00486.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)