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2018 | OriginalPaper | Buchkapitel

Recommender System Based on Fuzzy Reasoning and Information Systems

verfasst von : Martin Tabakov

Erschienen in: Computational Collective Intelligence

Verlag: Springer International Publishing

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Abstract

In this research a recommender system with possible applications in e-commerce, based on rule induction mechanism and fuzzy reasoning, is presented. The theoretical concept proposed assume the application of fuzzy sets in a procedure of rule induction, as an information generalization, in purpose to predict the degree of subjective customer satisfaction with respect to his previous reviews. The innovative idea lays in the transformation of decision rules into fuzzy rules, regarding to the basic Mamdani reasoning model. The research was verified on real data, i.e. customer reviews of different products.

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Fußnoten
1
The price attribute may not be up-to-date, but it doesn’t change the concept proposed.
 
Literatur
1.
Zurück zum Zitat du Boucher-Ryan, P., Bridge, D.: Collaborative recommending using formal concept analysis. Knowl.-Based Syst. 19(5), 309–315 (2006)CrossRef du Boucher-Ryan, P., Bridge, D.: Collaborative recommending using formal concept analysis. Knowl.-Based Syst. 19(5), 309–315 (2006)CrossRef
2.
Zurück zum Zitat Breese, J., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: UAI98, pp. 43–52 (1998) Breese, J., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: UAI98, pp. 43–52 (1998)
3.
Zurück zum Zitat Bronstein, I.N., Semendjajew, K.A., Musiol, G., Mühlig, H.: Taschenbuch der Mathematik, p. 1258. Harri Deutsch (2001) Bronstein, I.N., Semendjajew, K.A., Musiol, G., Mühlig, H.: Taschenbuch der Mathematik, p. 1258. Harri Deutsch (2001)
4.
Zurück zum Zitat Cao, Y., Li, Y.: An intelligent fuzzy-based recommendation system for consumer electronic products. Expert Syst. Appl. 33(1), 230–240 (2007)CrossRef Cao, Y., Li, Y.: An intelligent fuzzy-based recommendation system for consumer electronic products. Expert Syst. Appl. 33(1), 230–240 (2007)CrossRef
5.
Zurück zum Zitat Cheng, L.-C., Wang, H.-A.: A fuzzy recommender system based on the integration of subjective preferences and objective information. Appl. Soft Comput. 18, 290–301 (2014)CrossRef Cheng, L.-C., Wang, H.-A.: A fuzzy recommender system based on the integration of subjective preferences and objective information. Appl. Soft Comput. 18, 290–301 (2014)CrossRef
6.
Zurück zum Zitat Gediminas, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRef Gediminas, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRef
7.
Zurück zum Zitat Greg, L., Brent, S., Jeremy, Y.: Amazon.com recommendations: item-to-item collaborative filtering. IEEE Int. Comput. 7(1), 76–80 (2003)CrossRef Greg, L., Brent, S., Jeremy, Y.: Amazon.com recommendations: item-to-item collaborative filtering. IEEE Int. Comput. 7(1), 76–80 (2003)CrossRef
8.
Zurück zum Zitat Herlocker, J.L., Konstan, J.A., Borchers, A., Riedll, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the 1999 Conference on Research and Development in Information Retrieval (1999) Herlocker, J.L., Konstan, J.A., Borchers, A., Riedll, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the 1999 Conference on Research and Development in Information Retrieval (1999)
9.
Zurück zum Zitat Hofmann, T.: Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22(1), 89–115 (2004)CrossRef Hofmann, T.: Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22(1), 89–115 (2004)CrossRef
10.
Zurück zum Zitat Liu, D.R., Lai, C.H., Lee, W.J.: A hybrid of sequential rules and collaborative filtering for product recommendation. Inf. Sci. 179(2), 3505–3519 (2009)CrossRef Liu, D.R., Lai, C.H., Lee, W.J.: A hybrid of sequential rules and collaborative filtering for product recommendation. Inf. Sci. 179(2), 3505–3519 (2009)CrossRef
11.
Zurück zum Zitat Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud. 7(1), 1–13 (1975)CrossRef Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Man-Mach. Stud. 7(1), 1–13 (1975)CrossRef
12.
Zurück zum Zitat Morawski, J., et al.: A fuzzy recommender system for public library catalogs. Int. J. Intell. 32, 1062–1084 (2017)CrossRef Morawski, J., et al.: A fuzzy recommender system for public library catalogs. Int. J. Intell. 32, 1062–1084 (2017)CrossRef
13.
Zurück zum Zitat Pawlak, Z.: Information systems theoretical foundations. Inf. Syst. 6, 205–218 (1981)CrossRef Pawlak, Z.: Information systems theoretical foundations. Inf. Syst. 6, 205–218 (1981)CrossRef
14.
Zurück zum Zitat Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers Group, Dordrecht (1991)CrossRef Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers Group, Dordrecht (1991)CrossRef
15.
Zurück zum Zitat Porcel, C., Herrera-Viedma, E.: Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries. Knowl. Based Syst. 23(1), 32–39 (2010)CrossRef Porcel, C., Herrera-Viedma, E.: Dealing with incomplete information in a fuzzy linguistic recommender system to disseminate information in university digital libraries. Knowl. Based Syst. 23(1), 32–39 (2010)CrossRef
16.
Zurück zum Zitat Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of ACM Conference on Computer-Supported Cooperative Work, pp. 175–186 (1994) Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of ACM Conference on Computer-Supported Cooperative Work, pp. 175–186 (1994)
17.
Zurück zum Zitat Sarwar, B., Karypis, G., Konstan, J., Reidl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, Hong Kong, pp. 285–295 (2001) Sarwar, B., Karypis, G., Konstan, J., Reidl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, Hong Kong, pp. 285–295 (2001)
18.
Zurück zum Zitat Schafer, J.B., Konstan, J.A., Riedl, J.: E-commerce recommendation applications. Data Min. Knowl. Disc. 5(1), 115–153 (2001)CrossRef Schafer, J.B., Konstan, J.A., Riedl, J.: E-commerce recommendation applications. Data Min. Knowl. Disc. 5(1), 115–153 (2001)CrossRef
19.
Zurück zum Zitat Skowron, A., Suraj, Z.: A rough set approach to real-time state identification for decision making. Institute of computer science research, Report 18/93, Warsaw University of Technology (1993) Skowron, A., Suraj, Z.: A rough set approach to real-time state identification for decision making. Institute of computer science research, Report 18/93, Warsaw University of Technology (1993)
20.
Zurück zum Zitat Year, R., Martínez, L.: Fuzzy tools in recommender systems: a survey. Int. J. Comput. Intell. Syst. 10, 776–803 (2017)CrossRef Year, R., Martínez, L.: Fuzzy tools in recommender systems: a survey. Int. J. Comput. Intell. Syst. 10, 776–803 (2017)CrossRef
21.
Metadaten
Titel
Recommender System Based on Fuzzy Reasoning and Information Systems
verfasst von
Martin Tabakov
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-98443-8_23