ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 Spatiotemporal Pattern Mining Technique for Location-Based Service System
Cited 15 time in scopus Download 1 time Share share facebook twitter linkedin kakaostory
저자
부홍난, 이준욱, 류근호
발행일
200806
출처
ETRI Journal, v.30 no.3, pp.421-431
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.08.0107.0238
협약과제
07MD1400, USN 미들웨어 플랫폼 기술개발, 박종현
초록
In this paper, we offer a new technique to discover frequent spatiotemporal patterns from a moving object database. Though the search space for spatiotemporal knowledge is extremely challenging, imposing spatial and timing constraints on moving sequences makes the computation feasible. The proposed technique includes two algorithms, AllMOP and MaxMOP, to find all frequent patterns and maximal patterns, respectively. In addition, to support the service provider in sending information to a user in a push-driven manner, we propose a rule-based location prediction technique to predict the future location of the user. The idea is to employ the algorithm AllMOP to discover the frequent movement patterns in the user's historical movements, from which frequent movement rules are generated. These rules are then used to estimate the future location of the user. The performance is assessed with respect to precision and recall. The proposed techniques could be quite efficiently applied in a location-based service (LBS) system in which diverse types of data are integrated to support a variety of LBSs.
키워드
Location prediction, Location-based services, Movement pattern, Spatiotemporal data mining
KSP 제안 키워드
Data mining(DM), Location Prediction, Location-Based Services, Movement pattern, Moving object database, Precision and recall, Prediction technique, Rule-based, Search Space, Service Provider, Service System