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An Expressive Query Language for Product Recommender Systems

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Abstract

We argue that existing approaches to the construction of content-based Product Recommender Systems (Filter-Based Retrieval and Similarity-Based Retrieval) use inadequately expressive query languages. We introduce a new approach, which we call Order-Based Retrieval. We define and exemplify the six operators that constitute its query language. We show how these operators can better support the elicitation of both the customer's initial requirements and refinements to the initial requirements.

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References

  • Bergmann, R., Breen, S., Göker, M., Manago, M. & Wess, S. (1999). Developing Industrial Case-Based Reasoning Applications: The INRECA Methodology. Springer.

  • Bridge, D. (2001). Product Recommendation Systems: A New Direction. In Weber, R. & von Wangenheim, C. G. (eds.) Procs. of the Workshop Programme at the Fourth International Conference on Case-Based Reasoning, 79–86.

  • Burke, R. (2001). Ranking Algorithms for Costly Similarity Measures. In Aha, D. W. & Watson, I. (eds.) Case-Based Reasoning Research and Development (Procs. of the Fourth International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 2080, 105–117. Springer.

  • Burkhard, H.-D. (1998). Extending Some Concepts of CBR – Foundations of Case Retrieval Nets. In Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D. & Wess, S. (eds) Case-Based Reasoning Technology: From Foundations to Applications, Lecture Notes in Artificial Intelligence 1400, 17–50, Springer.

  • Codognet, P. & Rossi, F. (2000). Solving and Programming with Soft Constraints: Theory and Practice. Paper to accompany ECAI/AAAI Tutorial.

  • Cunningham, P., Bergmann, R., Schmitt, S., Breen, S., Smyth, B. & Traphöner, R. (2001). Intelligent Support for Online Sales: The WEBSELL Experience. In Weber, R. & von Wangenheim, C. G. (eds.) Procs. of the Workshop Programme at the Fourth International Conference on Case-Based Reasoning, 104–109.

  • Doyle, M. & Cunningham, P. (2000). A Dynamic Approach to Reducing Dialog in On-Line Decision Guides. In Blanzieri, E. & Portinale, L. (eds.) Advances in Case-Based Reaso-ning (Procs. of the Fifth European Workshop on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 1898, 49–60. Springer.

  • Ferguson, A. & Bridge, D. (1999). Generalised Prioritisation: A New Way of Combining Similarity Metrics. In Bridge, D., Byrne, R., O'sullivan, B., Prestwich, S. & Sorensen, H. (eds.) Procs. of Tenth Irish Conference on Artificial Intelligence & Cognitive Science, 137–142.

  • Ferguson, A. & Bridge, D. (2000). Partial Orders and Indifference Relations: Being Purpose-fully Vague in Case-Based Retrieval. In Blanzieri, E. & Portinale, L. (eds.) Advances in Case-Based Reasoning (Procs. of the Fifth European Workshop on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 1898, 74–85. Springer.

  • Ferguson, A. & Bridge, D. (2001). Weight Intervals: Conservatively adding quantified uncer-tainty to similarity. In O'Donoghue, D. (ed.) Procs. of the Twelfth Irish Conference on Artificial Intelligence & Cognitive Science, 75–84.

  • Freuder, E.C. & Wallace, R. J. (1998). Suggestion Strategies for Constraint-Based Match-maker Agents. In Rossi, F. (ed.) Principles and Practice of Constraint Programming (Procs. of the Fourth International Conference on Principles and Practice of Constraint Programming), Lecture Notes in Computer Science 1520, 192–204. Springer.

  • Hammond, K. J., Burke, R. & Schmitt, K. (1996). Case Based Approach to Knowledge Navigation. In Leake, D. B. (ed.) Case-Based Reasoning – Experiences, Lessons and Future Directions, 125–136. MIT Press.

  • Hurley, G. & Wilson, D. C. (2001). DubLet: An Online CBR System for Rental Property Accommodation. In Aha, D. W. & Watson, I. (eds.) Case-Based Reasoning Research and Development (Procs. of the Fourth International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 2080, 660–674. Springer.

  • Kohlmaier, A., Schmitt, S. & Bergmann, R. (2001). A Similarity-Based Approach to Attribute Selection in User-Adaptive Sales Dialogs. In Aha, D. W. & Watson, I. (eds.) Case-Based Reasoning Research and Development (Procs. of the Fourth International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 2080, 306–320. Springer.

  • Krantz, M. (1997). The Web's Middleman. Time February 17, 149(7): 67–68.

    Google Scholar 

  • McSherry, D. (2001). Minimizing Dialog Length in Interactive Case-Based Reasoning. In Nebel, B. (ed.) Procs. of the Seventeenth International Joint Conference on Artificial Intelligence, 993–998. Morgan Kaufmann.

  • Osborne, H.R. & Bridge, D. G. (1996). A Case Base Similarity Framework. In Smith, I. & Faltings, B. (eds.) Advances in Case-Based Reasoning (Procs. of the Third European Workshop on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 1168, 309–323. Springer.

  • Smyth, B. & McClave, P. (2001). Similarity vs. Diversity. In Aha, D. W. & Watson, I. (eds.) Case-Based Reasoning Research and Development (Procs. of the Fourth International Conference on Case-Based Reasoning), Lecture Notes in Artificial Intelligence 2080, 347–361. Springer.

  • Vollrath, I., Wilke, W. & Bergmann, R. (1998). Case-Based Reasoning Support for Online Catalog Sales. IEEE Internet Computing 2(4): 45–54.

    Google Scholar 

  • Weibelzahl, S., Bergmann, R. & Weber, G. (2000). Towards an Empirical Evaluation of CBR Approaches for Product Recommendation – In Electronic Shops. In Procs. of the Eighth German Workshop on Case-Based Reasoning, wwwagr.informatik.uni-kl.de/ ~`gwcbr2.

  • Wilke, W., Lenz, M. & Wess, S. (1998). Intelligent Sales Support with CBR. In Lenz, M., Bartsch-Spörl, B., Burkhard, H.-D. & Wess, S. (eds.) Case-Based Reasoning Technology: From Foundations to Applications, Lecture Notes in Artificial Intelligence 1400, 91–113. Springer.

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Bridge, D., Ferguson, A. An Expressive Query Language for Product Recommender Systems. Artificial Intelligence Review 18, 269–307 (2002). https://doi.org/10.1023/A:1020743321429

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  • DOI: https://doi.org/10.1023/A:1020743321429

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