SharedLife: Towards Selective Sharing of Augmented Personal Memories

  • Wolfgang Wahlster
  • Alexander Kröner
  • Dominik Heckmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4155)


The rapid deployment of low-cost ubiquitous sensing devices – including RFID tags and readers, global positioning systems, wireless audio, video, and bio sensors – makes it possible to create instrumented environments and to capture the physical and communicative interaction of an individual with these environments in a digital register. One of the grand challenges of current AI research is to process this multimodal and massive data stream, to recognize, classify, and represent its digital content in a context-sensitive way, and finally to integrate behavior understanding with reasoning and learning about the individual’s day by day experiences. This augmented personal memory is always accessible to its owner through an Internet-enabled smartphone using high-speed wireless communication technologies. In this contribution, we discuss how such an augmented personal memory can be built and applied for providing the user with context-related reminders and recommendations in a shopping scenario. With the ultimate goal of supporting communication between individuals and learning from the experiences of others, we apply this novel methods as the basis for a specific way of exploiting memories – the sharing of augmented personal memories in a way that doesn’t conflict with privacy constraints.


User Model Dynamic Bayesian Network Instrument Environment Privacy Constraint Personal Journal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Aizawa, K., Tancharoen, D., Kawasaki, S., Yamasaki, T.: Efficient retrieval of life log based on context and content. In: CARPE 2004: Proceedings of the the 1st ACM workshop on Continuous archival and retrieval of personal experiences, pp. 22–31. ACM Press, New York (2004)CrossRefGoogle Scholar
  2. 2.
    Amazon Inc. Amazon e-commerce service (April 2005),
  3. 3.
    Baldes, S., Kröner, A., Bauer, M.: Configuration and introspection of situated user support. In: LWA 2005, Lernen Wissensentdeckung Adaptivität, Saarland University, Saarbrücken, Germany, pp. 3–7 (2005)Google Scholar
  4. 4.
    Bauer, M., Baldes, S.: An Ontology-Based Interface for Machine Learning. In: Riedl, J., Jameson, A., Billsus, D., Lau, T. (eds.) IUI 2005: International Conference on Intelligent User Interfaces, pp. 314–316. ACM Press, New York (2005)CrossRefGoogle Scholar
  5. 5.
    Brandherm, B., Schultheis, H., von Wilamowitz-Moellendorff, M., Schwartz, T., Schmitz, M.: Using physiological signals in a user-adaptive personal assistant. In: Proceedings of the 11th International Conference on Human-Computer Interaction (HCII 2005), Las Vegas, Nevada, USA (2005)Google Scholar
  6. 6.
    Brandherm, B., Schwartz, T.: Geo referenced dynamic bayesian networks for user positioning on mobile systems. In: Strang, T., Linnhoff-Popien, C. (eds.) LoCA 2005. LNCS, vol. 3479, pp. 223–234. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  7. 7.
    Clarkson, B.: Life Patterns: structure from wearable sensors. PhD thesis, School of Architecture and Planning, Massachusetts Institute of Technology, Cambridge, MA (2002)Google Scholar
  8. 8.
    Dumais, S., Cutrell, E., Cadiz, J., Jancke, G., Sarin, R., Robbins, D.C.: Stuff i’ve seen: a system for personal information retrieval and re-use. In: SIGIR 2003: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp. 72–79. ACM Press, New York (2003)CrossRefGoogle Scholar
  9. 9.
    Gemmell, J., Williams, L., Wood, K., Lueder, R., Bell, G.: Passive Capture and Ensuing Issues for a Personal Lifetime Store. In: Proceedings of The First ACM Workshop on Continuous Archival and Retrieval of Personal Experiences (CARPE 2004), New York, USA, pp. 48–55 (2004)Google Scholar
  10. 10.
    Heckmann, D.: Ubiquitous User Modeling. PhD thesis, Department of Computer Science, Saarland University, Germany (2005)Google Scholar
  11. 11.
    Heckmann, D., Schwartz, T., Brandherm, B., Schmitz, M., von Wilamowitz-Moellendorff, M.: GUMO - the general user model ontology. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 428–432. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  12. 12.
    Horvitz, E., Dumais, S., Koch, P.: Learning predictive models of memory landmarks. In: Proceedings of the CogSci 2004: 26th Annual Meeting of the Cognitive Science Society, Chicago, USA (August 2004)Google Scholar
  13. 13.
    Huber, M.J.: JAM: A BDI-theoretic mobile agent architecture. In: AGENTS 1999: Proceedings of the third annual conference on Autonomous Agents, pp. 236–243. ACM Press, New York (1999)CrossRefGoogle Scholar
  14. 14.
    Kay, J., Kummerfeld, B., Lauder, P.: Personis: A server for user models. In: De Bra, P., Brusilovsky, P., Conejo, R. (eds.) AH 2002. LNCS, vol. 2347, pp. 203–212. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  15. 15.
    Kröner, A., Heckmann, D., Wahlster, W.: SPECTER: Building, exploiting, and sharing augmented memories. In: Workshop on Knowledge Sharing for Everyday Life 2006 (KSEL 2006), Kyoto, Japan, February 2006. ATR Media Information Science Laboratories, pp. 9–16 (2006) (invited talk)Google Scholar
  16. 16.
    Kuwahara, N., Noma, H., Kogure, K., Hagita, N., Tetsutani, N., Iseki, H.: Wearable auto-event-recording of medical nursing. In: Proceedings of the Ninth IFIP TC13 International Conference on Human-Computer Interaction, INTERACT 2003 (September 2003)Google Scholar
  17. 17.
    Lamming, M., Flynn, M.: “Forget-Me-Not”: Intimate computing in support of human memory. In: Proceedings of FRIEND21, the 1994 International Symposium on Next Generation Human Interface, Meguro Gajoen, Japan (1994)Google Scholar
  18. 18.
    Niles, I., Pease, A.: Towards a standard upper ontology. In: FOIS 2001: Proceedings of the international conference on Formal Ontology in Information Systems, pp. 2–9. ACM Press, New York (2001)CrossRefGoogle Scholar
  19. 19.
    Philipose, M., Fishkin, K.P., Perkowitz, M., Patterson, D., Hähnel, D.: The probabilistic activity toolkit: Towards enabling activity-aware computer interfaces. Technical Report IRS-TR-03-013, Intel Research Seattle, Seattle, WA 98115, USA (2003)Google Scholar
  20. 20.
    Plate, C., Basselin, N., Kröner, A., Schneider, M., Baldes, S., Dimitrova, V., Jameson, A.: Recomindation: New functions for augmented memories. In: Wade, V.P., Ashman, H., Smyth, B. (eds.) AH 2006. LNCS, vol. 4018, pp. 141–150. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  21. 21.
    Schneider, M.: RDF: Stores – A lightweight approach on managing shared knowledge. In: Ma, J., Jin, H., Yang, L.T., Tsai, J.J.-P. (eds.) UIC 2006. LNCS, vol. 4159, pp. 229–239. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  22. 22.
    Sharples, M., Hogg, D., Hutchinson, C., Torrance, S.: Computers and Thought: A Practical Introduction to Artificial Intelligence. Bradford Book (1989)Google Scholar
  23. 23.
    Stathis, K., de Bruijn, O., Macedo, S.: Living memory: agent-based information management for connected local communities. Interacting with Computers 14(6), 663–688 (2002)CrossRefGoogle Scholar
  24. 24.
    Sumi, Y., Mase, K.: Supporting awareness of shared interests and experiences in community. International Journal of Human-Computer Studies 56(1), 127–146 (2002)CrossRefGoogle Scholar
  25. 25.
    Wasinger, R., Wahlster, W.: The anthropomorphized product shelf: Symmetric multimodal interaction with instrumented environments. In: Aarts, E., Encarnação, J. (eds.) True Visions: The Emergence of Ambient Intelligence. Springer, Heidelberg (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wolfgang Wahlster
    • 1
  • Alexander Kröner
    • 1
  • Dominik Heckmann
    • 1
  1. 1.German Research Center for Artificial Intelligence (DFKI) GmbHSaarbrückenGermany

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