Development of a novel context prediction algorithm and analysis of context prediction schemes

Context-awareness is an area in which we strive to improve the environmentapplication interaction by the consideration of environmental stimuli and with focus on the application’s reaction. The aim is to extend the knowledge of applications on the requirements of a given situation beyond explicit inputs. This approach is motivated by the general observation that a given environment greatly impacts the intention with which an application is executed. Consider, for example, the ringing profile of a mobile phone. When a user is in a meeting, she will prefer a silent mode while in between two meetings she might be willing to be notified of incoming calls by a ring tone. The preference of the ringing profile of the user is situation dependent. In context-awareness, the environmental situation is recorded with the help of sensors. One of the vital parts is then to extract valuable information from this knowledge. This extracted information helps to fine-tune the reaction to the user needs in an ever more advanced manner. Context-awareness is a broad field that can be further partitioned into sub-disciplines that themselves constitute interesting research topics. A context-aware application might be aware of its present, past or future context. Most work is carried out taking present or past context into consideration. A research branch that is by far less intensively studied is the derivation and utilisation of future context. The latter research topic is commonly referred to as context prediction. In this thesis we investigate issues related to the inference of future context and to the utilisation of past and present contexts in this setting. We discuss the context prediction task and identify chances and challenges that derive from it. This discussion leads to a definition of the context prediction task. The context prediction task might be completed by various context prediction schemes. Dependent on the amount of pre-processing or context abstraction applied to context data, we distinguish between various context prediction schemes. We study context prediction schemes for their prediction accuracy and provide guidelines to application designers as to

[1]  Claude Sammut,et al.  Learning in Time Ordered Domains with Hidden Changes in Context , 2000 .

[2]  M. COTTRELL SIMULATING INTEREST RATE STRUCTURE EVOLUTION ON A LONG TERM HORIZON A KOHONEN MAP APPLICATION , .

[3]  Vinny Cahill,et al.  Towards a Sentient Object Model , 2002 .

[4]  Gerd Kortuem,et al.  Context-aware, adaptive wearable computers as remote interfaces to 'intelligent' environments , 1998, Digest of Papers. Second International Symposium on Wearable Computers (Cat. No.98EX215).

[5]  Artemis Papakyriazis,et al.  Adaptive prediction: a sequential approach to forecasting and estimation of nonstationary environmental systems , 1999 .

[6]  Johan Himberg,et al.  From Insights to Innovations: Data Mining, Visualization, and User Interfaces , 2022 .

[7]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[8]  Heikki Mannila,et al.  Time series segmentation for context recognition in mobile devices , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[9]  Bill N. Schilit,et al.  Context-aware computing applications , 1994, Workshop on Mobile Computing Systems and Applications.

[10]  Gudberg K. Jonsson,et al.  Detection of real-time patterns in sports interactions in football , 2002 .

[11]  Mika Raento,et al.  Adaptive On-Device Location Recognition , 2004, Pervasive.

[12]  William Noah Schilit,et al.  A system architecture for context-aware mobile computing , 1995 .

[13]  Alexander De Luca,et al.  Analysis of Built-in Mobile Phone Sensors for Supporting Interactions with the Real World , 2005, PERMID.

[14]  Stephan Sigg,et al.  A Novel Approach to Context Prediction in UBICOMP Environments , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[15]  W R Pearson,et al.  Flexible sequence similarity searching with the FASTA3 program package. , 2000, Methods in molecular biology.

[16]  Gilles Pagès,et al.  Theoretical aspects of the SOM algorithm , 1998, Neurocomputing.

[17]  Tan Yee Fan,et al.  A Tutorial on Support Vector Machine , 2009 .

[18]  Stephan Sigg,et al.  The Quick Step to Foxtrot , 2006 .

[19]  Eugene H. Spafford,et al.  Authorship analysis: identifying the author of a program , 1997, Comput. Secur..

[20]  Haym Hirsh,et al.  Learning to Predict Rare Events in Categorical Time-Series Data , 1998 .

[21]  Michael Beigl,et al.  The MediaCup: Awareness Technology Embedded in a Everyday Object , 1999, HUC.

[22]  Albrecht Schmidt,et al.  Context Acquisition Based on Load Sensing , 2002, UbiComp.

[23]  Alois Ferscha Pervasive Computing - Kurz erklärt , 2003, Datenbank-Spektrum.

[24]  Richard A. Davis,et al.  Introduction to time series and forecasting , 1998 .

[25]  Stephan Sigg,et al.  Context Prediction by Alignment Methods , 2006 .

[26]  T. Kohonen Analysis of a simple self-organizing process , 1982, Biological Cybernetics.

[27]  T. Kohonen Self-organized formation of topology correct feature maps , 1982 .

[28]  Gregory D. Abowd,et al.  CyberDesk: a framework for providing self-integrating context-aware services , 1998, Knowl. Based Syst..

[29]  Kishan G. Mehrotra,et al.  Elements of artificial neural networks , 1996 .

[30]  Jukka Heikkonen,et al.  Recurrent SOM with local linear models in time series prediction , 1998, ESANN.

[31]  Brian D. Davison,et al.  Predicting Sequences of User Actions , 1998 .

[32]  Mahadev Satyanarayanan,et al.  Using history to improve mobile application adaptation , 2000, Proceedings Third IEEE Workshop on Mobile Computing Systems and Applications.

[33]  Andreas Pietzowski,et al.  Prediction of Indoor Movements Using Bayesian Networks , 2005, LoCA.

[34]  Cecilia Mascolo,et al.  Evaluating context information predictability for autonomic communication , 2006, 2006 International Symposium on a World of Wireless, Mobile and Multimedia Networks(WoWMoM'06).

[35]  Kristof Van Laerhoven,et al.  What shall we teach our pants? , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[36]  Ben Y. Zhao,et al.  Pond: The OceanStore Prototype , 2003, FAST.

[37]  Paul Dourish,et al.  What we talk about when we talk about context , 2004, Personal and Ubiquitous Computing.

[38]  Arpad Gellert,et al.  Person Movement Prediction Using Neural Networks , 2004 .

[39]  Eugene W. Myers,et al.  Basic local alignment search tool. Journal of Molecular Biology , 1990 .

[40]  David Garlan,et al.  Project Aura: Toward Distraction-Free Pervasive Computing , 2002, IEEE Pervasive Comput..

[41]  Bernard Burg,et al.  Towards a general approach for reasoning about context situations and uncertainty in ubiquitous sensing : putting geometrical intuitions to work , 2004 .

[42]  Gregory D. Abowd,et al.  Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.

[43]  Henry A. Kautz,et al.  Inferring High-Level Behavior from Low-Level Sensors , 2003, UbiComp.

[44]  Jan Petzold Zustandsprädiktoren zur Kontextvorhersage in ubiquitären Systemen , 2005 .

[45]  Se-Hak Chun,et al.  Impact of momentum bias on forecasting through knowledge discovery techniques in the foreign exchange market , 2003, Expert Syst. Appl..

[46]  John R. Anderson Cognitive Psychology and Its Implications , 1980 .

[47]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..

[48]  Arkady B. Zaslavsky,et al.  On Uncertainty in Context-Aware Computing: Appealing to High-Level and Same-Level Context for Low-Level Context Verification , 2004, IWUC.

[49]  C. Randell,et al.  Context awareness by analysing accelerometer data , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[50]  Cecilia Mascolo,et al.  Predictive Resource Scheduling in Computational Grids , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[51]  Michael C. Mozer,et al.  Neural net architectures for temporal sequence processing , 2007 .

[52]  Albrecht Schmidt,et al.  Ubiquitous computing - computing in context , 2003 .

[53]  M. Beigl,et al.  There is more to Context than Location Environment Sensing Technologies for Adaptive Mobile User Interfaces , 1998 .

[54]  Teuvo Kohonen,et al.  In: Self-organising Maps , 1995 .

[55]  David Poole,et al.  Predicting Future User Actions by Observing Unmodified Applications , 2000, AAAI/IAAI.

[56]  Alois Ferscha,et al.  Context Sensing, Aggregation, Representation and Exploitation in Wireless Networks , 2001, Scalable Comput. Pract. Exp..

[57]  Bill N. Schilit,et al.  Disseminating active map information to mobile hosts , 1994, IEEE Network.

[58]  Jason Pascoe,et al.  Adding generic contextual capabilities to wearable computers , 1998, Digest of Papers. Second International Symposium on Wearable Computers (Cat. No.98EX215).

[59]  Wolfgang Trumler,et al.  Confidence Estimation of the State Predictor Method , 2004, EUSAI.

[60]  Kristof Van Laerhoven,et al.  Context awareness in Systems with Limited Resources , 2002 .

[61]  Michel Verleysen,et al.  Forecasting time-series by Kohonen classification , 1998, ESANN.

[62]  Bill N. Schilit,et al.  An overview of the PARCTAB ubiquitous computing experiment , 1995, IEEE Wirel. Commun..

[63]  Anton Schwaighofer,et al.  The Bayesian Committee Support Vector Machine , 2001, ICANN.

[64]  Gregory D. Abowd,et al.  Providing architectural support for building context-aware applications , 2000 .

[65]  Richard Han,et al.  Automated Selection of the Active Device in Interactive Multi-Device Smart Spaces , 2002 .

[66]  Henk L. Muller,et al.  The Well Mannered Wearable Computer , 2002, Personal and Ubiquitous Computing.

[67]  J. Karam,et al.  Methods in Nucleic Acids Research , 1990 .

[68]  Diane J. Cook,et al.  MavHome: an agent-based smart home , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[69]  Michel Verleysen,et al.  Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection , 1999, IWANN.

[70]  A. Akhmetova Discovery of Frequent Episodes in Event Sequences , 2006 .

[71]  Donald A. Norman,et al.  The invisible computer , 1998 .

[72]  Guanling Chen,et al.  Solar: Building A Context Fusion Network for Pervasive Computing , 2004 .

[73]  Licia Capra,et al.  Autonomic trust prediction for pervasive systems , 2006, 20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06).

[74]  Diane J. Cook,et al.  Improving home automation by discovering regularly occurring device usage patterns , 2003, Third IEEE International Conference on Data Mining.

[75]  Petteri Nurmi,et al.  Enabling proactiveness through context prediction , 2005 .

[76]  Henry Lieberman,et al.  Out of context: Computer systems that adapt to, and learn from, context , 2000, IBM Syst. J..

[77]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1971 .

[78]  Albrecht Schmidt,et al.  Multi-sensor context aware clothing , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[79]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[80]  Stephan Sigg,et al.  Minimising the Context Prediction Error , 2007, 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring.

[81]  Mahadev Satyanarayanan,et al.  Scalable, secure, and highly available distributed file access , 1990, Computer.

[82]  Eric Horvitz,et al.  Attention-Sensitive Alerting , 1999, UAI.

[83]  Theo Ungerer,et al.  Processor architecture - from dataflow to superscalar and beyond , 1999 .

[84]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[85]  Diane J. Cook,et al.  Active Lezi: an Incremental Parsing Algorithm for Sequential Prediction , 2004, Int. J. Artif. Intell. Tools.

[86]  Heikki Mannila,et al.  Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.

[87]  Chris Chatfield,et al.  The Analysis of Time Series: An Introduction , 1981 .

[88]  Graham Cutts Three men in a boat : film , 1933 .

[89]  Neri Merhav,et al.  Universal prediction of individual sequences , 1992, IEEE Trans. Inf. Theory.

[90]  Peter J. Brown,et al.  Context-aware applications: from the laboratory to the marketplace , 1997, IEEE Wirel. Commun..

[91]  Carl Gold,et al.  Bayesian approach to feature selection and parameter tuning for support vector machine classifiers , 2005, Neural Networks.

[92]  Ben Y. Zhao,et al.  OceanStore: an architecture for global-scale persistent storage , 2000, SIGP.

[93]  Peter Steenkiste,et al.  Providing contextual information to pervasive computing applications , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[94]  A. Padovitz,et al.  1 Extending the Context Space Approach to Management by Business Objectives , 2005 .

[95]  Gareth J. F. Jones,et al.  Exploiting contextual change in context-aware retrieval , 2002, SAC '02.

[96]  Ian Taylor,et al.  Unearthing Virtual History: Using Diverse Interfaces to Reveal Hidden Virtual Worlds , 2001, UbiComp.

[97]  Eamonn J. Keogh,et al.  An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback , 1998, KDD.

[98]  Thomas Jansen,et al.  Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Perhaps Not a Free Lunch but at Least a Free Appetizer Perhaps Not a Free Lunch but at Least a Free Appetizer , 2022 .

[99]  T. Ungerer,et al.  Next Location Prediction Within a Smart Office Building , 2005 .

[100]  Gregory D. Abowd,et al.  A Context-Based Infrastructure for Smart Environments , 2000 .

[101]  Jason Pascoe,et al.  The stick-e note architecture: extending the interface beyond the user , 1997, IUI '97.

[102]  Steve Benford,et al.  The Frame of the Game: Blurring the Boundary between Fiction and Reality in Mobile Experiences , 2006, CHI 2006.

[103]  D. Kimbrough Oller,et al.  Evolution of communication systems : a comparative approach , 2004 .

[104]  Michel Verleysen,et al.  Time series forecasting: Obtaining long term trends with self-organizing maps , 2005, Pattern Recognit. Lett..

[105]  William H. Hsu,et al.  Heterogeneous Time Series Learning for Crisis Monitoring , 1998 .

[106]  Hans-Joachim Böckenhauer,et al.  Algorithmische Grundlagen der Bioinformatik , 2003 .

[107]  Rene Mayrhofer,et al.  An architecture for context prediction , 2004 .

[108]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[109]  Saul Greenberg,et al.  Context as a Dynamic Construct , 2001, Hum. Comput. Interact..

[110]  P. A. Blight The Analysis of Time Series: An Introduction , 1991 .

[111]  Jani Mäntyjärvi,et al.  Sensor-based context recognition for mobile applications , 2003 .

[112]  Anne Lohrli Chapman and Hall , 1985 .

[113]  Alois Ferscha,et al.  Recognizing and Predicting Context by Learning from User Behavior 1 , 2003 .

[114]  Gregory D. Abowd,et al.  The Conference Assistant: combining context-awareness with wearable computing , 1999, Digest of Papers. Third International Symposium on Wearable Computers.

[115]  Alois Ferscha,et al.  Orientation sensing for gesture-based interaction with smart artifacts , 2005, Comput. Commun..

[116]  S. Martin,et al.  Using context prediction for self-management in ubiquitous computing environments , 2006, CCNC 2006. 2006 3rd IEEE Consumer Communications and Networking Conference, 2006..

[117]  Johan Himberg,et al.  Collaborative context recognition for handheld devices , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[118]  Michael C. Mozer,et al.  The Neural Network House: An Environment that Adapts to its Inhabitants , 1998 .

[119]  Teuvo Kohonen,et al.  Self-Organization and Associative Memory , 1988 .

[120]  Uwe Hansmann,et al.  Pervasive Computing , 2003 .

[121]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[122]  Iven Mareels,et al.  Reducing the computational load of a Kalman filter , 1997 .

[123]  Patrick Rousset,et al.  Forecasting of curves using a Kohonen classification , 1998 .

[124]  Thad Starner,et al.  Learning Significant Locations and Predicting User Movement with GPS , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[125]  Helen J. Wang,et al.  The Iceberg project: defining the IP and telecom intersection , 1999 .

[126]  Hiroshi Ishii,et al.  A tangible interface for organizing information using a grid , 2002, CHI.

[127]  James A. Cadzow,et al.  Adaptive ARMA spectral estimation , 1981, ICASSP.

[128]  T. Moore,et al.  The Life of Lord Byron: With His Letters and Journals , 2010 .

[129]  Barry A. T. Brown,et al.  Building a Context Sensitive Telephone: Some Hopes and Pitfalls for Context Sensitive Computing , 2004, Computer Supported Cooperative Work (CSCW).

[130]  A. Ferscha,et al.  A Peer-to-Peer Light-Weight Component Model for Context-Aware Smart Space Applications , 2004 .

[131]  Se-Hak Chun,et al.  Data mining for financial prediction and trading: application to single and multiple markets , 2004, Expert Syst. Appl..

[132]  Peter Brown Context-awareness: some compelling applications , 2000 .

[133]  Ingo Wegener,et al.  Theoretische Informatik - eine algorithmenorientierte Einführung , 1993, Leitfäden und Monographien der Informatik.

[134]  S. B. Needleman,et al.  A general method applicable to the search for similarities in the amino acid sequence of two proteins. , 1970, Journal of molecular biology.

[135]  Helen J. Wang,et al.  ICEBERG: an Internet core network architecture for integrated communications , 2000, IEEE Wirel. Commun..

[136]  Duncan Rowland,et al.  Interweaving mobile games with everyday life , 2006, CHI.

[137]  Jörg A. Walter,et al.  Nonlinear prediction with self-organizing maps , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[138]  Pragya Agarwal,et al.  Self-Organising Maps , 2008 .

[139]  Magnus S. Magnusson,et al.  Repeated Patterns in Behavior and Other Biological Phenomena , 2004 .

[140]  Louise Barkhuus How to Define the Communication Situation : Context Measures in Present Mobile Telephony , 2003 .

[141]  Karen Henricksen,et al.  A framework for context-aware pervasive computing applications , 2003 .

[142]  R. Mayrhofer Context Prediction based on Context Histories : Expected Benefits , Issues and Current State-ofthe-Art , 2005 .

[143]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[144]  Albrecht Schmidt,et al.  Multi-Sensor Context-Awareness in Mobile Devices and Smart Artifacts , 2002, Mob. Networks Appl..

[145]  Eric Horvitz,et al.  Coordinates: Probabilistic Forecasting of Presence and Availability , 2002, UAI.

[146]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[147]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[148]  Alois Ferscha,et al.  Interfaces everywhere: interacting with the pervasive computer , 2006, IUI '06.

[149]  Henk L. Muller,et al.  Low Cost Indoor Positioning System , 2001, UbiComp.