Browse > Article

A Design of Context Prediction Structure using Homogeneous Feature Extraction  

Kim, Hyung-Sun (공주대학교 컴퓨터공학과)
Im, Kyoung-Mi (공주대학교 대학원 전자계산학과)
Lim, Jae-Hyun (공주대학교 컴퓨터공학부)
Publication Information
Journal of Internet Computing and Services / v.11, no.4, 2010 , pp. 85-94 More about this Journal
Abstract
In this paper, we propose a location-prediction structure that can provide user service in advance. It consists of seven steps and supplies intelligent services which can forecast user's location. Context information collected from physical sensors and a history database is so difficult that it can't present importance of data and abstraction of data because of heterogeneous data type. Hence, we offer the location-prediction that change data type from heterogeneous data to homogeneous data. Extracted data is clustered by SOFM, then it gets user's location information by ARIMA and realizes the services by a reasoning engine. In order to validate the proposed location-prediction, we built a test-bed and test it by the scenario.
Keywords
prediction; location-prediction; SOFM; ARIMA; time series analysis;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 이종섭, 강맹규, `자기조직화 신경망의 정렬된 연결강도를 이용한 클러스터링 알고리즘', 한국경영과학회지 제31권 3호, pp41-51, 2006.   과학기술학회마을
2 Mayrhofer, R., Radi, H., Ferscha, A., 'Recognizing and Predicting Context by Learning from User Behavior', Journal of Communication Engineering, special issue on Advances in Mobile Multimedia, Vol.1 No.1, 2004.
3 Contreras, J., Espinola, R., Nogales, F.J., Conejo, A.J., 'ARIMA Models to Project Next-Day Electricity Prices', IEEE Transactions on Power Systems, Vol.18 No.3, pp.1014-1020, 2003.   DOI   ScienceOn
4 Cho, S. B. and Ryu, J. W., `Classifying gene expression data of cancer using classifier ensemble with mutually exclusive features', Proceeding of the IEEE, Vol.90 No.11, pp.1744-1753, 2002.
5 Kohonen, T., 'Self-Organizing Maps', Springer, Berlin, 1997.
6 임재현, '지능형 서비스를 위한 상황인식 해석 구조 설계 및 구현', 한국인터넷정보학회논문지 제7권 5호, pp123-134, 2006   과학기술학회마을
7 정동빈, 'SPSS 시계열 수요예측 I', 한나래아카데미, 2009.
8 김형선, 이준연, 김치수, 김황래, 임재현, "모바일 서비스를 위한 상황 예측 시스템", 한국인터넷정보학회 추계대회 논문집 제 10권 제2호, pp 77-81, 2009
9 Mantyjarvi, J., `Sensor-based context recognition for mobile applications', PhD thesis, VTT Technical Research Centre of Finland, 2003.
10 Mayrhofer, R., 'An Architecture for Context Prediction', PhD thesis, Johannes Kepeler University of Linz, Altenbergstrasse 69, 4040 Linz, Austria, 2004.
11 David, K., Ferscha, A., `Development of a novel context prediction algorithm and analysis of context prediction schemes', kassel university press, 2008.
12 Gellersen H.W., Schmidt, A. and Beigl, M. `Multi-sensor context-awareness in mobile devices and smart artefacts', Accepted for publication in Mobile Networks and Applications, 2003.
13 Mayrhofer, R., Radi, H. and Ferscha, A. `Feature extraction in wireless personal and local area networks', Proceedings of the Fifth IFIP TC6 International Conference on Mobile and Wireless Communications Network (MWCN 2003), World Scientific., pp195-198, 2003.
14 Park, D., Hwang, S., Kim, A. and Chang, B., 'Context-Aware Smart Tourist Guide Application for an Old Place', ICCIT 2007, 2007.
15 Lau, S.L., Klein, N., Pirali, A., Konig, I., David, K.,`Implementation of a User-Centric Context-Aware Playground', Electronic Communications of the EASST, Vol.17, 2009.
16 Petzold, J., Bagci, F., Trumler, W., Ungerer, T., 'Next location prediction within a smart office building', In: 1st International Workshop on Exploiting Context Histories in Smart Environments (ECHISE) at the 3rd Int, Conference on Pervasive Computing, 2005.
17 Villalonga, C., Strohbach, M., Snoeck, N., Sutterer, M., Belaunde, M., Kovacs, E., Zhdanova, A.V., Goix, L.W., Droegehorn, O., 'Mobile Ontology: Towards a Standardized Semantic Model for the Mobile Domain', ICSOC 2007, Service-oriented computing, pp.248-257, 2009.