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2016 | OriginalPaper | Buchkapitel

5. Knowledge-Based Recommender Systems

verfasst von : Charu C. Aggarwal

Erschienen in: Recommender Systems

Verlag: Springer International Publishing

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Abstract

Both content-based and collaborative systems require a significant amount of data about past buying and rating experiences. For example, collaborative systems require a reasonably well populated ratings matrix to make future recommendations. In cases where the amount of available data is limited, the recommendations are either poor, or they lack full coverage over the entire spectrum of user-item combinations.

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Fußnoten
1
Content-based systems are used both in the information retrieval and the relational settings, whereas knowledge-based systems are used mostly in the relational setting.
 
Literatur
[18]
Zurück zum Zitat C. Aggarwal. Data classification: algorithms and applications. CRC Press, 2014. C. Aggarwal. Data classification: algorithms and applications. CRC Press, 2014.
[23]
Zurück zum Zitat C. Aggarwal and J. Han. Frequent pattern mining. Springer, New York, 2014. C. Aggarwal and J. Han. Frequent pattern mining. Springer, New York, 2014.
[31]
Zurück zum Zitat C. Aggarwal, Z. Sun, and P. Yu. Online generation of profile association rules. ACM KDD Conference, pp. 129–133, 1998. C. Aggarwal, Z. Sun, and P. Yu. Online generation of profile association rules. ACM KDD Conference, pp. 129–133, 1998.
[32]
Zurück zum Zitat C. Aggarwal, Z. Sun, and P. Yu. Online algorithms for finding profile association rules, CIKM Conference, pp. 86–95, 1998. C. Aggarwal, Z. Sun, and P. Yu. Online algorithms for finding profile association rules, CIKM Conference, pp. 86–95, 1998.
[74]
Zurück zum Zitat R. Bergmann, M. Richter, S. Schmitt, A. Stahl, and I. Vollrath. Utility-oriented matching: a new research direction for case-based reasoning. German Workshop on Case-Based Reasoning, pp. 264–274, 2001. R. Bergmann, M. Richter, S. Schmitt, A. Stahl, and I. Vollrath. Utility-oriented matching: a new research direction for case-based reasoning. German Workshop on Case-Based Reasoning, pp. 264–274, 2001.
[94]
Zurück zum Zitat K. Bradley and B. Smyth. Improving recommendation diversity. National Conference in Artificial Intelligence and Cognitive Science, pp. 75–84, 2001. K. Bradley and B. Smyth. Improving recommendation diversity. National Conference in Artificial Intelligence and Cognitive Science, pp. 75–84, 2001.
[95]
Zurück zum Zitat K. Bradley, R. Rafter, and B. Smyth. Case-based user profiling for content personalization. International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 62–72, 2000. K. Bradley, R. Rafter, and B. Smyth. Case-based user profiling for content personalization. International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 62–72, 2000.
[97]
Zurück zum Zitat L. Branting. Acquiring customer preferences from return-set selections. Case-Based Reasoning Research and Development, pp. 59–73, 2001. L. Branting. Acquiring customer preferences from return-set selections. Case-Based Reasoning Research and Development, pp. 59–73, 2001.
[101]
Zurück zum Zitat D. Bridge. Diverse product recommendations using an expressive language for case retrieval. European Conference on Case-Based Reasoning, pp. 43–57. 2002. D. Bridge. Diverse product recommendations using an expressive language for case retrieval. European Conference on Case-Based Reasoning, pp. 43–57. 2002.
[102]
Zurück zum Zitat D. Bridge, M. Goker, L. McGinty, and B. Smyth. Case-based recommender systems. The Knowledge Engineering Review, 20(3), pp. 315–320, 2005.CrossRef D. Bridge, M. Goker, L. McGinty, and B. Smyth. Case-based recommender systems. The Knowledge Engineering Review, 20(3), pp. 315–320, 2005.CrossRef
[116]
Zurück zum Zitat R. Burke. Knowledge-based recommender systems. Encyclopedia of library and information systems, pp. 175–186, 2000. R. Burke. Knowledge-based recommender systems. Encyclopedia of library and information systems, pp. 175–186, 2000.
[117]
Zurück zum Zitat R. Burke. Hybrid recommender systems: Survey and experiments. User Modeling and User-adapted Interaction, 12(4), pp. 331–370, 2002.CrossRefMATH R. Burke. Hybrid recommender systems: Survey and experiments. User Modeling and User-adapted Interaction, 12(4), pp. 331–370, 2002.CrossRefMATH
[120]
Zurück zum Zitat R. Burke, K. Hammond, and B. Young. Knowledge-based navigation of complex information spaces. National Conference on Artificial Intelligence, pp. 462–468, 1996. R. Burke, K. Hammond, and B. Young. Knowledge-based navigation of complex information spaces. National Conference on Artificial Intelligence, pp. 462–468, 1996.
[121]
Zurück zum Zitat R. Burke, K. Hammond, and B. Young. The FindMe approach to assisted browsing. IEEE Expert, 12(4), pp. 32–40, 1997.CrossRef R. Burke, K. Hammond, and B. Young. The FindMe approach to assisted browsing. IEEE Expert, 12(4), pp. 32–40, 1997.CrossRef
[125]
Zurück zum Zitat R. Burke. The Wasabi personal shopper: a case-based recommender system. National Conference on Innovative Applications of Artificial Intelligence, pp. 844–849, 1999. R. Burke. The Wasabi personal shopper: a case-based recommender system. National Conference on Innovative Applications of Artificial Intelligence, pp. 844–849, 1999.
[149]
Zurück zum Zitat L. Chen and P. Pu. Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction, 22(1–2), pp. 125–150, 2012.CrossRef L. Chen and P. Pu. Critiquing-based recommenders: survey and emerging trends. User Modeling and User-Adapted Interaction, 22(1–2), pp. 125–150, 2012.CrossRef
[155]
Zurück zum Zitat Y. Chen, I. Hsu, and C. Lin. Website attributes that increase consumer purchase intention: a conjoint analysis. Journal of Business Research, 63(9), pp. 1007–1014, 2010.CrossRef Y. Chen, I. Hsu, and C. Lin. Website attributes that increase consumer purchase intention: a conjoint analysis. Journal of Business Research, 63(9), pp. 1007–1014, 2010.CrossRef
[163]
Zurück zum Zitat W. Cohen, R. Schapire and Y. Singer. Learning to order things. Advances in Neural Information Processing Systems, pp. 451–457, 2007. W. Cohen, R. Schapire and Y. Singer. Learning to order things. Advances in Neural Information Processing Systems, pp. 451–457, 2007.
[170]
Zurück zum Zitat L. Coyle and P. Cunningham. Improving recommendation ranking by learning personal feature weights. European Conference on Case-Based Reasoning, Springer, pp. 560–572, 2004. L. Coyle and P. Cunningham. Improving recommendation ranking by learning personal feature weights. European Conference on Case-Based Reasoning, Springer, pp. 560–572, 2004.
[196]
Zurück zum Zitat A. Felfernig and R. Burke. Constraint-based recommender systems: technologies and research issues. International conference on Electronic Commerce, 2008. (p. A. Felfernig and R. Burke. Constraint-based recommender systems: technologies and research issues. International conference on Electronic Commerce, 2008. (p.
[197]
Zurück zum Zitat A. Felfernig, G. Friedrich, D. Jannach, and M. Zanker. Developing constraint-based recommenders. Recommender Systems Handbook, Springer, pp. 187–216, 2011. A. Felfernig, G. Friedrich, D. Jannach, and M. Zanker. Developing constraint-based recommenders. Recommender Systems Handbook, Springer, pp. 187–216, 2011.
[198]
Zurück zum Zitat A. Felfernig, G. Friedrich, D. Jannach, and M. Stumptner. Consistency-based diagnosis of configuration knowledge bases. Artificial Intelligence, 152(2), 213–234, 2004.MathSciNetCrossRefMATH A. Felfernig, G. Friedrich, D. Jannach, and M. Stumptner. Consistency-based diagnosis of configuration knowledge bases. Artificial Intelligence, 152(2), 213–234, 2004.MathSciNetCrossRefMATH
[199]
Zurück zum Zitat A. Felfernig, G. Friedrich, M. Schubert, M. Mandl, M. Mairitsch, and E. Teppan. Plausible repairs for inconsistent requirements. IJCAI Conference, pp. 791–796, 2009. A. Felfernig, G. Friedrich, M. Schubert, M. Mandl, M. Mairitsch, and E. Teppan. Plausible repairs for inconsistent requirements. IJCAI Conference, pp. 791–796, 2009.
[200]
Zurück zum Zitat A. Felfernig, E. Teppan, E., and B. Gula. Knowledge-based recommender technologies for marketing and sales. International Journal of Pattern Recognition and Artificial Intelligence, 21(02), pp. 333–354, 2007. A. Felfernig, E. Teppan, E., and B. Gula. Knowledge-based recommender technologies for marketing and sales. International Journal of Pattern Recognition and Artificial Intelligence, 21(02), pp. 333–354, 2007.
[201]
Zurück zum Zitat A. Felfernig, K. Isak, K. Szabo, and P. Zachar. The VITA financial services sales support environment. National conference on artificial intelligence, 22(2), pp. 1692–1699, 2007. A. Felfernig, K. Isak, K. Szabo, and P. Zachar. The VITA financial services sales support environment. National conference on artificial intelligence, 22(2), pp. 1692–1699, 2007.
[263]
Zurück zum Zitat G. Hurley and D. Wilson. DubLet: An online CBR system for rental property accommodation. International Conference on Case-Based Reasoning, pp. 660–674, 2001. G. Hurley and D. Wilson. DubLet: An online CBR system for rental property accommodation. International Conference on Case-Based Reasoning, pp. 660–674, 2001.
[273]
Zurück zum Zitat D. Jannach. Finding preferred query relaxations in content-based recommenders. Intelligent Techniques and Tools for Novel System Architectures, Springer, pp. 81–97, 2006. D. Jannach. Finding preferred query relaxations in content-based recommenders. Intelligent Techniques and Tools for Novel System Architectures, Springer, pp. 81–97, 2006.
[274]
Zurück zum Zitat D. Jannach. Techniques for fast query relaxation in content-based recommender systems. Advances in Artificial Intelligence, Springer, pp. 49–63, 2006. D. Jannach. Techniques for fast query relaxation in content-based recommender systems. Advances in Artificial Intelligence, Springer, pp. 49–63, 2006.
[279]
Zurück zum Zitat Z. Jiang, W. Wang, and I. Benbasat. Multimedia-based interactive advising technology for online consumer decision support. Communications of the ACM, 48(9), pp. 92–98, 2005.CrossRef Z. Jiang, W. Wang, and I. Benbasat. Multimedia-based interactive advising technology for online consumer decision support. Communications of the ACM, 48(9), pp. 92–98, 2005.CrossRef
[288]
Zurück zum Zitat P. Juell and P. Paulson. Using reinforcement learning for similarity assessment in case-based systems. IEEE Intelligent Systems, 18(4), pp. 60–67, 2003.CrossRef P. Juell and P. Paulson. Using reinforcement learning for similarity assessment in case-based systems. IEEE Intelligent Systems, 18(4), pp. 60–67, 2003.CrossRef
[289]
Zurück zum Zitat U. Junker. QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems. AAAI Conference, pp. 167–172, 2004. U. Junker. QUICKXPLAIN: preferred explanations and relaxations for over-constrained problems. AAAI Conference, pp. 167–172, 2004.
[320]
Zurück zum Zitat B. Krulwich. Lifestyle finder: Intelligent user profiling using large-scale demographic data. AI Magazine, 18(2), pp. 37–45, 1995. B. Krulwich. Lifestyle finder: Intelligent user profiling using large-scale demographic data. AI Magazine, 18(2), pp. 37–45, 1995.
[377]
Zurück zum Zitat F. Lorenzi and F. Ricci. Case-based recommender systems: a unifying view. Intelligent Techniques for Web Personalization, pp. 89–113, Springer, 2005. F. Lorenzi and F. Ricci. Case-based recommender systems: a unifying view. Intelligent Techniques for Web Personalization, pp. 89–113, Springer, 2005.
[389]
Zurück zum Zitat T. Mahmood and F. Ricci. Learning and adaptivity in interactive recommender systems. International Conference on Electronic Commerce, pp. 75–84, 2007. T. Mahmood and F. Ricci. Learning and adaptivity in interactive recommender systems. International Conference on Electronic Commerce, pp. 75–84, 2007.
[390]
Zurück zum Zitat T. Mahmood and F. Ricci. Improving recommender systems with adaptive conversational strategies. ACM Conference on Hypertext and Hypermedia, pp. 73–82, 2009. T. Mahmood and F. Ricci. Improving recommender systems with adaptive conversational strategies. ACM Conference on Hypertext and Hypermedia, pp. 73–82, 2009.
[414]
Zurück zum Zitat K. McCarthy, J. Reilly, L. McGinty, and B. Smyth. On the dynamic generation of compound critiques in conversational recommender systems. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 176–184, 2004. K. McCarthy, J. Reilly, L. McGinty, and B. Smyth. On the dynamic generation of compound critiques in conversational recommender systems. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 176–184, 2004.
[416]
Zurück zum Zitat K. McCarthy, L. McGinty, and B. Smyth. Dynamic critiquing: an analysis of cognitive load. Irish Conference on Artificial Intelligence and Cognitive Science, pp. 19–28, 2005. K. McCarthy, L. McGinty, and B. Smyth. Dynamic critiquing: an analysis of cognitive load. Irish Conference on Artificial Intelligence and Cognitive Science, pp. 19–28, 2005.
[417]
Zurück zum Zitat L. McGinty and J. Reilly. On the evolution of critiquing recommenders. Recommender Systems Handbook, pp. 419–453, 2011. L. McGinty and J. Reilly. On the evolution of critiquing recommenders. Recommender Systems Handbook, pp. 419–453, 2011.
[419]
Zurück zum Zitat D. McSherry. Incremental relaxation of unsuccessful queries. Advances in Case-Based Reasoning, pp. 331–345, 2004. D. McSherry. Incremental relaxation of unsuccessful queries. Advances in Case-Based Reasoning, pp. 331–345, 2004.
[420]
Zurück zum Zitat D. McSherry. Diversity-Conscious Retrieval. European Conference on Case-Based Reasoning, pp. 219–233, 2002. D. McSherry. Diversity-Conscious Retrieval. European Conference on Case-Based Reasoning, pp. 219–233, 2002.
[421]
Zurück zum Zitat D. McSherry. Similarity and Compromise. International Conference on Case-Based Reasoning, pp. 291–305, 2003. D. McSherry. Similarity and Compromise. International Conference on Case-Based Reasoning, pp. 291–305, 2003.
[422]
Zurück zum Zitat D. McSherry and D. Aha. The ins and outs of critiquing. IJCAI, pp. 962–967, 2007. D. McSherry and D. Aha. The ins and outs of critiquing. IJCAI, pp. 962–967, 2007.
[423]
Zurück zum Zitat D. McSherry and D. Aha. Avoiding long and fruitless dialogues in critiquing. Research and Development in Intelligent Systems, pp. 173–186, 2007. D. McSherry and D. Aha. Avoiding long and fruitless dialogues in critiquing. Research and Development in Intelligent Systems, pp. 173–186, 2007.
[454]
Zurück zum Zitat Q. Nguyen and F. Ricci. User preferences initialization and integration in critique-based mobile recommender systems. Artificial Intelligence in Mobile Systems, pp. 71–78, 2004. Q. Nguyen and F. Ricci. User preferences initialization and integration in critique-based mobile recommender systems. Artificial Intelligence in Mobile Systems, pp. 71–78, 2004.
[483]
Zurück zum Zitat B. Polak, A. Herrmann, M. Heitmann, and M. Einhorn. Die Macht des Defaults – Wirkung von Empfehlungen und Vorgaben auf das individuelle Entscheidungsverhalten. [English Translation: The power of defaults: Effect on individual choice behavior.] Zeitschrift fur Betriebswirtschaft, 78(10), pp. 1033–1060, 2008. B. Polak, A. Herrmann, M. Heitmann, and M. Einhorn. Die Macht des Defaults – Wirkung von Empfehlungen und Vorgaben auf das individuelle Entscheidungsverhalten. [English Translation: The power of defaults: Effect on individual choice behavior.] Zeitschrift fur Betriebswirtschaft, 78(10), pp. 1033–1060, 2008.
[491]
Zurück zum Zitat J. Reilly, B. Smyth, L. McGinty, and K. McCarthy. Critiquing with confidence. Case-Based Reasoning Research and Development, pp. 436–450, 2005. J. Reilly, B. Smyth, L. McGinty, and K. McCarthy. Critiquing with confidence. Case-Based Reasoning Research and Development, pp. 436–450, 2005.
[492]
Zurück zum Zitat J. Reilly, K. McCarthy, L. McGinty, and B. Smyth. Explaining compound critiques. Artificial Intelligence Review, 24(2), pp. 199–220, 2005.CrossRef J. Reilly, K. McCarthy, L. McGinty, and B. Smyth. Explaining compound critiques. Artificial Intelligence Review, 24(2), pp. 199–220, 2005.CrossRef
[506]
Zurück zum Zitat F. Ricci and P. Avesani. Learning a local similarity metric for case-based reasoning. International Conference on Case-Based Reasoning Research and Development, pp. 301–312, 1995. F. Ricci and P. Avesani. Learning a local similarity metric for case-based reasoning. International Conference on Case-Based Reasoning Research and Development, pp. 301–312, 1995.
[507]
Zurück zum Zitat F. Ricci, B. Arslan, N. Mirzadeh, and A. Venturini. LTR: A case-based travel advisory system. European Conference on Case-Based Reasoning, pp. 613–627, 2002. F. Ricci, B. Arslan, N. Mirzadeh, and A. Venturini. LTR: A case-based travel advisory system. European Conference on Case-Based Reasoning, pp. 613–627, 2002.
[531]
Zurück zum Zitat L. Schaupp and F. Belanger. A conjoint analysis of online consumer satisfaction. Journal of Electronic Commerce Research, 6(2), pp. 95–111, 2005. L. Schaupp and F. Belanger. A conjoint analysis of online consumer satisfaction. Journal of Electronic Commerce Research, 6(2), pp. 95–111, 2005.
[550]
Zurück zum Zitat H. Shimazu, A. Shibata, and K. Nihei. ExpertGuide: A conversational case-based reasoning tool for developing mentors in knowledge spaces. Applied Intelligence, 14(1), pp. 33–48, 2002.CrossRefMATH H. Shimazu, A. Shibata, and K. Nihei. ExpertGuide: A conversational case-based reasoning tool for developing mentors in knowledge spaces. Applied Intelligence, 14(1), pp. 33–48, 2002.CrossRefMATH
[558]
Zurück zum Zitat B. Smyth. Case-based recommendation. The Adaptive Web, pp. 342–376, Springer, 2007. B. Smyth. Case-based recommendation. The Adaptive Web, pp. 342–376, Springer, 2007.
[560]
Zurück zum Zitat B. Smyth and P. McClave. Similarity vs. diversity. Case-Based Reasoning Research and Development, pp. 347–361, 2001. B. Smyth and P. McClave. Similarity vs. diversity. Case-Based Reasoning Research and Development, pp. 347–361, 2001.
[563]
Zurück zum Zitat A. Stahl. Learning feature weights from case order feedback. International Conference on Case-Based Reasoning, pp. 502–516, 2001. A. Stahl. Learning feature weights from case order feedback. International Conference on Case-Based Reasoning, pp. 502–516, 2001.
[574]
Zurück zum Zitat B. O’Sullivan, A. Papadopoulos, B. Faltings, and P. Pu. Representative explanations for over-constrained problems. AAAI Conference, pp. 323–328, 2007. B. O’Sullivan, A. Papadopoulos, B. Faltings, and P. Pu. Representative explanations for over-constrained problems. AAAI Conference, pp. 323–328, 2007.
[627]
Zurück zum Zitat D. Wettschereck and D. Aha. Weighting features. International Conference on Case-Based Reasoning, pp. 347–358. 1995. D. Wettschereck and D. Aha. Weighting features. International Conference on Case-Based Reasoning, pp. 347–358. 1995.
[641]
Zurück zum Zitat H. Xie, L. Chen, and F. Wang. Collaborative Compound Critiquing. User Modeling, Adaptation, and Personalization, Springer, pp. 254–265, 2014. H. Xie, L. Chen, and F. Wang. Collaborative Compound Critiquing. User Modeling, Adaptation, and Personalization, Springer, pp. 254–265, 2014.
[664]
Zurück zum Zitat J. Zhang and P. Pu. A comparative study of compound critique generation in conversational recommender systems. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 234–243, Springer, 2006. J. Zhang and P. Pu. A comparative study of compound critique generation in conversational recommender systems. Adaptive Hypermedia and Adaptive Web-Based Systems, pp. 234–243, Springer, 2006.
[665]
Zurück zum Zitat J. Zhang, N. Jones, and P. Pu. A visual interface for critiquing-based recommender systems. Proceedings of the ACM conference on Electronic Commerce, pp. 230–239, 2008. J. Zhang, N. Jones, and P. Pu. A visual interface for critiquing-based recommender systems. Proceedings of the ACM conference on Electronic Commerce, pp. 230–239, 2008.
Metadaten
Titel
Knowledge-Based Recommender Systems
verfasst von
Charu C. Aggarwal
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-29659-3_5