Packet-based context aware system to determine information system user's context

Expert Systems with Applications

Volumn 35, Issue 1-2, 2008, Pages 286-300

  Kang, Hyeon ^a   Suh, Euiho ^b   Yoo, Keedong ^c  

^a POSDATA Co Ltd   (South Korea)

^b Pohang University of Science and Technology (POSTECH)   (South Korea)

^c Dankook University   (South Korea)

Author keywords

Context aware systems; Context inference; Internal context; Packet capturing technique; Support Vector Machine

Indexed keywords

ALGORITHMS; BOOLEAN FUNCTIONS; COMPUTATIONAL METHODS; COMPUTER NETWORKS; COMPUTERS; EVOLUTIONARY ALGORITHMS; INFERENCE ENGINES; INFORMATION SCIENCE; INFORMATION SYSTEMS; INFORMATION TECHNOLOGY; INTERNET; MERGERS AND ACQUISITIONS; METROPOLITAN AREA NETWORKS; NETWORK PROTOCOLS; PAPER; RESEARCH; SCHEDULING ALGORITHMS;

COMPUTING RESEARCH; CONTEXT ACQUISITION; CONTEXT AWARENESS (CA); CONTEXT-AWARE SYSTEMS; ELSEVIER (CO); IN ORDER; INFERENCE ALGORITHMS; INFORMATION SYSTEM (IS); INTERNET BASED; NETWORK TECHNIQUES; PROTOTYPE SYSTEMS; UBIQUITOUS SERVICES;

UBIQUITOUS COMPUTING;

EID: 44949257350     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.06.033     Document Type: Article

References (23)

1. Ansari S., Rajeev S.G., and Chandrashekar H.S. Packet sniffing - A brief introduction. Potentials, IEEE 21 5 (2002) 17-19
2. Budzik J., Hammond K.J., and Birnbaum L. Information access in context. Knowledge-based Systems 14 1-2 (2001) 37-53
3. Chang, C. C., Lin, C.-J. (2001). LIBSVM: a library for Support Vector Machines. Software available at http://www.csie.ntu.edu.tw/_cjlin/libsvm.
4. Chen R.C., and Hsieh C.H. Web page classification based on a Support Vector Machine using a weighted vote schema. Expert Systems with Applications 31 2 (2006) 427-435
5. Cortes C., and Vapnik V. Support-vector networks. Machine Learning 20 3 (1995) 273-297
6. Dey, A. K., Abowd, G. D. (1999). Towards a better understanding of context and context-awareness. Proceedings of the 2000 conference on human factors in computing systems (CHI2000) workshop 11.
7. Gunnn, S. R. (1998). Support Vector Machines for classification and regression. ISIS technical report.
8. Gwizdka, J. (2000). What's in the context? Proceedings of the 2000 conference on human factors in computing systems (CHI0-) workshop11.
9. Hsu, C. W., Chang, C. C., Lin, C. J. (2001). A practical guide to support vector classification, LibSVM Tutorial. Available at http://www.csie.ntu.edu.tw/~cjlin/papers/guide/guide.pdf.
10. Joachims, T. (1998). Text categorization with Support Vector Machines: Learning with many relevant features. Proceedings of ECML-98, 10th European conference on machine learning (pp. 137-142).
11. Kim, S. J., Suh, E. H., Yoo, K. D. (2005). A study of context inference algorithm on the web-based information system. Proceedings of pacific asia conference on information systems.
12. Kurose J.F., and Ross K.W. Computer networking: A top-down approach featuring the internet. 3rd ed. (2005), Addition Wesley
13. Kwon O., Choi S.C., and Park G.R. NAMA: A context-aware multi-agent based web service approach to proactive need identification for personalized reminder systems. Expert Systems with Applications 29 1 (2005) 17-32
14. McCarty B. Honeypot forensics part 1. Analyzing the network. IEEE Security & Privacy Magazine 2 4 (2004) 72-78
15. Prekop P., and Burnet M. Activities, context and ubiquitous computing. Computer Communications 26 11 (2003) 1168-1176
16. Pressman R.S. Software engineering: a practitioner's approach. 6h ed. (2005), McGraw-Hill
17. Salton G., Wong A., and Yang C. A vector space model for automatic indexing. Communications of the ACM 18 11 (1975) 61-620
18. Schilit, B. N., Adams N., Want R. (1994). Context-aware computing applications. Proceedings of IEEE workshop on mobile computing systems and applications (pp. 85-90).
19. Schmidt A., Beigl M., and Gellersen H.W. There is more to context than location. Computers and Graphics 23 6 (1999) 893-901
20. Wurst, M. (2005). The Word Vector Tool: A Java library for creating vector representations of text documents. Available at http://yale.cs.uni-dormund.de/.
21. Wurst, M. The Word Vector Tool. (accessed 10.12.2006).
22. WinPcap. (accessed 01.12.2006).
23. Yang, Y., Liu, X. (1999). A re-examination of text categorization methods. Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval (pp. 42-49).