A multi-dimensional indexing approach for timestamped event sequence matching
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Sanghyun | - |
dc.contributor.author | Won, Jung Im | - |
dc.contributor.author | Yoon, Jee Hee | - |
dc.contributor.author | Kim, Sang Wook | - |
dc.date.accessioned | 2022-12-21T05:36:26Z | - |
dc.date.available | 2022-12-21T05:36:26Z | - |
dc.date.created | 2022-08-26 | - |
dc.date.issued | 2007-11 | - |
dc.identifier.issn | 0020-0255 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/179409 | - |
dc.description.abstract | This paper addresses the problem of timestamped event sequence matching, a new type of similar sequence matching that retrieves the occurrences of interesting patterns from timestamped sequence databases. The sequential-scan-based method, the trie-based method, and the method based on the iso-depth index are well-known approaches to this problem. In this paper, we point out their shortcomings, and propose a new method that effectively overcomes these shortcomings. The proposed method employs an R*-tree, a widely accepted multi-dimensional index structure that efficiently supports timestamped event sequence matching. To build the R*-tree, this method extracts time windows from every item in a timestamped event sequence and represents them as rectangles in n-dimensional space by considering the first and last occurring times of each event type. Here, n is the total number of disparate event types that may occur in a target application. To resolve the dimensionality curse in the case when n is large, we suggest an algorithm for reducing the dimensionality by grouping the event types. Our sequence matching method based on the R*-tree performs with two steps. First, it efficiently identifies a small number of candidates by searching the R*-tree. Second, it picks out true answers from the set of candidates. We prove its robustness formally, and also show its effectiveness via extensive experiments. (C) 2007 Elsevier Inc. All rights reserved. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE INC | - |
dc.title | A multi-dimensional indexing approach for timestamped event sequence matching | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sang Wook | - |
dc.identifier.doi | 10.1016/j.ins.2007.06.020 | - |
dc.identifier.scopusid | 2-s2.0-34548258670 | - |
dc.identifier.wosid | 000250016200002 | - |
dc.identifier.bibliographicCitation | INFORMATION SCIENCES, v.177, no.22, pp.4859 - 4876 | - |
dc.relation.isPartOf | INFORMATION SCIENCES | - |
dc.citation.title | INFORMATION SCIENCES | - |
dc.citation.volume | 177 | - |
dc.citation.number | 22 | - |
dc.citation.startPage | 4859 | - |
dc.citation.endPage | 4876 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.subject.keywordPlus | TIME | - |
dc.subject.keywordPlus | QUERIES | - |
dc.subject.keywordAuthor | sequence database | - |
dc.subject.keywordAuthor | event sequence | - |
dc.subject.keywordAuthor | timestamped event sequence matching | - |
dc.subject.keywordAuthor | similar sequence matching | - |
dc.subject.keywordAuthor | multi-dimensional index | - |
dc.identifier.url | https://www.sciencedirect.com/science/article/pii/S0020025507003179?via%3Dihub | - |
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