This Article 
 Bibliographic References 
 Add to: 
An Alignment Approach for Context Prediction Tasks in UbiComp Environments
October-December 2010 (vol. 9 no. 4)
pp. 90-97
Stephan Sigg, Technische Universität Braunschweig
Sandra Haseloff, Alexander von Humboldt Foundation
Klaus David, University of Kassel
The authors detail the alignment prediction approach—a time-series-estimation technique applicable to both numeric and nonnumeric data—and compare it to four other prediction approaches to determine context-prediction accuracy in ubiquitous computing environments.

1. S. Sigg, Development of a Novel Context Prediction Algorithm and Analysis of Context Prediction Schemes, University of Kassel Press, 2008.
2. K. Gopalratnam and D.J. Cook, "Active Lezi: An Incremental Parsing Algorithm for Sequential Prediction," Int'l J. Artificial Intelligence Tools, vol. 14, nos. 1–2, 2004, pp. 917–930.
3. G. Simon et al., "Time Series Forecasting: Obtaining Long Term Trends with Self-Organising Maps," Pattern Recognition Letters, vol. 26, no. 12, 2005, pp. 1795–1808.
4. R.M. Mayrhofer, "An Architecture for Context Prediction," doctoral dissertation, Institute for Pervasive Computing, Johannes Kepeler Univ. of Linz, 2004.
5. J. Petzold et al., "Prediction of Indoor Movements Using Bayesian Networks," 1st Int'l Workshop Location and Context Awareness (LoCA 05), Springer, 2005, pp. 211–222.
6. M.C. Mozer, "Neural Net Architectures for Temporal Sequence Processing," Predicting the Future Understanding the Past, A.S. Weigend, and N.A. Gershenfeld eds., Addison-Wesley, 1994.
7. N. Eagle, and A.S. Pentland, "Eigenbehaviors: Identifying Structure in Routine," Behavioral Ecology and Sociobiology, vol. 63, no. 7, 2009, pp. 1057–1066.
8. L. Capra and M. Musolesi, "Autonomic Trust Prediction for Pervasive Systems," Proc. 20th Int'l Conf. Advanced Information Networking and Applications (AINA 06), vol. 2, IEEE CS Press, 2006, pp. 481–488.
9. H.-J. Boeckenhauer and D. Bongartz, Algorithmische Grundlagen der Bioinformatik, Teubner, 2003 (in German).
10. P.A. Pevzner, Computational Molecular Biology—An Algorithmic Approach, MIT Press, 2000.
11. S.B. Needleman and C.D. Wunsch, "A General Method Applicable to the Search for Similarities in the Amino Acid Sequence of Two Proteins," J. Molecular Biology, vol. 48, no. 3, 1970, pp. 443–453.
12. S.F. Altschul et al., "Basic Local Alignment Search Tool," J. Molecular Biology, vol. 215, no. 3, 1990, pp. 403–410.
13. S.F. Altschul et al., "Gapped Blast and Psi-Blast: A New Generation of Protein Database Search Programs," Nucleic Acids Research, vol. 25, no. 17, 1997, pp. 3389–3402.
14. W.R. Pearson, "Flexible Sequence Similarity Searching with the Fasta3 Program Package," Methods in Molecular Biology, vol. 132, no. 2, 2000, pp. 185–219.
15. M. Feder, N. Merhav, and M. Gutman, "Universal Prediction of Individual Sequences," IEEE Trans. Information Theory, vol. 38, no. 4, 1992, pp. 1258–1270.
16. D.L. Vail, M.M. Veloso, and J.D. Lafferty, "Conditional Random Fields for Activity Recognition," Proc. 6th Int'l Joint Conf. Autonomous Agents and Multiagent Systems (AAMAS 07), ACM Press, 2007, pp. 1–8.
17. S. Roweis and Z. Ghahramani, "A Unifying Review of Linear Gaussian Models," Neural Computation, vol. 11, no. 2, 1999, pp. 305–345.
18. D.J. Patterson et al., "Inferring High-Level Behaviour from Low-Level Sensors," 5th Int'l Conf. Ubiquitous Computing (UbiComp 03), vol. 5, Springer, 2003, pp. 73–89.
19. J.A. Cadzow and K. Ogino, "Adaptive ARMA Spectral Estimation," Proc. IEEE Int'l Conf. Acoustics, Speech, and Signal Processing (ICASSP 81), vol. 6, IEEE Press, 1981, pp. 475–479.
20. R. Jursa, B. Lange, and K. Rohrig, "Advanced Wind Power Prediction with Artificial Intelligence Methods," Artificial Intelligence in Energy Systems and Power (AIESP 2006), ICSC Interdisciplinary Research, 2006, pp. 1–10.
21. M. Turk and A.S. Pentland, "Eigenfaces for Recognition," J. Cognitive Neuroscience, vol. 3, no. 1, 1991, pp. 71–86.
22. Q. Du and J.E. Fowler, "Low-Complexity Principal Component Analysis for Hyperspectral Image Compression," J. High Performance Computing Applications, vol. 22, no. 4, 2008, pp. 438–448.
23. A. Hyvaerinen and E. Oja, "Independent Component Analysis: Algorithms and Applications," Neural Networks, vol. 13, nos. 4–5, 2000, pp. 411–430.
24. S. Shwartz, M. Zibulevsky, and Y.Y. Schechner, "ICA Using Kernel Entropy Estimation with nlogn Complexity," LNCS 3195, Springer, 2004, pp. 422–429.
25. N. Eagle and A.S. Pentland, "Reality Mining: Sensing Complex Social Systems," Personal Ubiquitous Computing, vol. 10, no. 4, 2006, pp. 255–268.

Index Terms:
Pervasive computing, pattern recognition algorithms, location-dependent and sensitive, discrete event simulation
Stephan Sigg, Sandra Haseloff, Klaus David, "An Alignment Approach for Context Prediction Tasks in UbiComp Environments," IEEE Pervasive Computing, vol. 9, no. 4, pp. 90-97, Oct.-Dec. 2010, doi:10.1109/MPRV.2010.23
Usage of this product signifies your acceptance of the Terms of Use.