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Situationsgerechtes Recommending

Kontextadaptive, hybride Empfehlungsgenerierung

  • HAUPTBEITRAG
  • SITUATIONSGERECHTES RECOMMENDING
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Informatik-Spektrum Aims and scope

Zusammenfassung

Dieser Artikel untersucht die unterschiedlichen Paradigmen, die kontextadaptiven Empfehlungssystemen zugrunde liegen und schlägt einen neuen perspektivenorientierten Ansatz vor. Kontext kann demnach nicht nur als vorab festgelegte Menge vorliegender Gegebenheiten (repräsentationaler Ansatz) oder in Wechselwirkung zur aktuellen Tätigkeit (interaktionaler Ansatz) gesehen werden, sondern als eine sich dynamisch ändernde Perspektive, unter der eine vorliegende Situation zu beurteilen ist. Mit Context Views führen wir eine Methode ein, mit der auf diese Weise kontextsensitive Empfehlungen generiert werden können. Weiterhin wird ein Framework vorgestellt, das in flexibler Weise kontextabhängig unterschiedliche Strategien zur Empfehlungsgenerierung in einem hybriden Ansatz integrieren kann.

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References

  1. Adomavicius G, Sankaranarayanan R, Sen S, Tuzhilin A (2005) Incorporating contextual information in recommender systems using a multidimensional approach. ACM Trans Inf Syst 23(1):103–145

    Article  Google Scholar 

  2. Anand S, Mobasher B (2007) Contextual recommendation. In: From Web to Social Web: Discovering and Deploying User and Content Profiles. Springer, pp 142–160

  3. Burke R (2002) Hybrid recommender systems: survey and experiments. User Model User-Adapted Interact 12(4):331–370

    Article  MATH  Google Scholar 

  4. Candillier L, Jack K, Fessant F, Meyer F (2009) Collaborative and Social Information Retrieval and Access: Techniques for Improved User Modeling, chapter State-of-the-Art Recommender Systems. Idea Group Publishing

  5. Chi E (2004) Transient user profiling. In: Proceedings of the Workshop on User Profiling (held in conjunction with CHI 2004)

  6. Dey AK, Abowd GD (2000) Towards a better understanding of context and context-awareness. In: Proceedings of the CHI 2000 Workshop on the What, Who, Where, When, and How of Context-Awareness. ACM Press, The Hague, Netherlands

    Google Scholar 

  7. Dourish P (2004) What we talk about when we talk about context. Pers Ubiquitous Comput 8(1):19–30

    Article  Google Scholar 

  8. Goldberg D, Nichols D, Oki BM, Terry D (1992) Using collaborative filtering to weave an information tapestry. Commun ACM 35(12):61–70

    Article  Google Scholar 

  9. Haake J, Hussein T, Joop B, Lukosch S, Veiel D, Ziegler J (2010) Modeling and exploiting context for adaptive collaboration. Int J Cooperative Inf Syst 19(1–2):71–120

    Article  Google Scholar 

  10. Herlocker JL, Konstan JA (2001) Content-independent task-focused recommendation. IEEE Internet Comput 5(6):40–47

    Article  Google Scholar 

  11. Hussein T, Ziegler J (2008) Adapting web sites by spreading activation in ontologies. In: Proceedings of the International Workshop on Recommendation and Collaboration, ACM, New York, USA

  12. Hussein T, Linder T, Gaulke W, Ziegler J (2009) Context-aware recommendations on rails. In: Workshop on Context-Aware Recommender Systems (CARS-2009) in conjunction with the 3rd ACM Conference on Recommender Systems (ACM RecSys 2009), New York, NY, USA

  13. Hussein T, Linder T, Gaulke W, Ziegler J (2010) A framework and an architecture for context-aware group recommendations. In: Kolfschoten G, Herrmann T, Lukosch S (eds) CRIWG 2010: Proceedings of the 16th Conference on Collaboration and Technology, Lect Notes Comput Sci 6257

  14. Jin X, Zhou Y, Mobasher B (2005) Task-oriented web user modeling for recommendation. In: UM 2005: 10th International Conference on User Modeling, Lect Notes Comput Sci 3538:109–118

  15. Kim S, Kwon J (2007) Effective context-aware recommendation on the semantic web. Int J Comput Sci Network Secur 7(8):154–159

    MathSciNet  Google Scholar 

  16. Lieberman H, Selker T (2000) Out of context: computer systems that adapt to, and learn from, context. IBM Syst J 39(3–4):617–632

    Article  Google Scholar 

  17. Münter D, Hussein T (2011) Adaptive presentation of itineraries in navigation systems by means of semantic models. 2nd International Workshop on Semantic Models for Adaptive Interactive Systems (SEMAIS) 2011

  18. Reichling T, Veith M, Wulf V (2007) Expert Recommender: designing for a network organisation. CSCW 16(4–5):431–465

    Google Scholar 

  19. Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl J (1994) Grouplens: an open architecture for collaborative filtering of netnews. In: CSCW ’94: Proceedings of the 1994 ACM conference on Computer supported cooperative work, ACM, New York, NY, USA, pp 175–186

  20. Sarwar B, Karypis G, Konstan J, Riedl J (2000) Analysis of recommendation algorithms for e-commerce. In: EC ’00: Proceedings of the 2nd ACM conference on Electronic commerce, ACM, New York, NY, USA, pp 158–167

  21. Sarwar B, Karypis G, Konstan JA, Riedl JT (2001) Item-based collaborative filtering recommendation algorithms. In: Shen VY, Saito N, Lyu MR, Zurko ME (eds) Proceedings of the 10th international conference on World Wide Web, ACM, Hong Kong, pp 285–295

  22. Suchman L (1987) Plans and Situated Actions: The Problem of Human-Machine Communication. Cambridge University Press, New York, NY, USA

    Google Scholar 

  23. Wade W (2003) A grocery cart that holds bread, butter and preferences. New York Times, 16. Januar

Download references

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Correspondence to Tim Hussein.

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Hussein, T., Ziegler, J. Situationsgerechtes Recommending. Informatik Spektrum 34, 143–152 (2011). https://doi.org/10.1007/s00287-011-0523-1

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  • DOI: https://doi.org/10.1007/s00287-011-0523-1

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