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Explanation of Recommenders Using Formal Concept Analysis

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Case-Based Reasoning Research and Development (ICCBR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11680))

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Abstract

Formal Concept Analysis is a mathematical approach which enables formalisation of concepts as basic units of human thinking and analysing data in the object-attribute form. In this paper, we propose the use of FCA as a general resource for explanations and apply it to explain the results of recommender systems. Our method is reusable and applicable to different domains. We define different types of explanations by travelling the lattice structure and analyse how the lattice metrics can be used to characterise the different types of user profiles.

Supported by the UCM (Research Group 921330), the Spanish Committee of Economy and Competitiveness (TIN2017-87330-R) and the fundings provided by Banco Santander in UCM (CT17/17-CT17/18) and (CT42/18-CT43/18).

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Notes

  1. 1.

    Conexp tool (https://sourceforge.net/projects/conexp/).

  2. 2.

    https://www.imdb.com/.

References

  1. Aamodt, A.: Explanation-driven case-based reasoning. In: Wess, S., Althoff, K.-D., Richter, M.M. (eds.) EWCBR 1993. LNCS, vol. 837, pp. 274–288. Springer, Heidelberg (1994). https://doi.org/10.1007/3-540-58330-0_93

    Chapter  Google Scholar 

  2. Armengol, E., Plaza, E.: Using symbolic descriptions to explain similarity on CBR. In: Proceedings of the 8th International Conference of the ACIA, Alguer, Italy, pp. 239–246 (2005)

    Google Scholar 

  3. Bell, R., Koren, Y., Volinsky, C.: Matrix factorization techniques for recommender systems. Computer 42(08), 30–37 (2009)

    Article  Google Scholar 

  4. Biran, O., Cotton, C.V.: Explanation and justification in machine learning: a survey. In: IJCAI 2017 Workshop on Explainable AI (XAI) (2017)

    Google Scholar 

  5. Birkhoff, G.: Lattice Theory, vol. 25. American Mathematical Society, New York (1940)

    MATH  Google Scholar 

  6. Caro-Martinez, M., Jimenez-Diaz, G., Recio-Garcia, J.A.: A theoretical model of explanations in recommender systems. In: ICCBR 2018, p. 52 (2018)

    Google Scholar 

  7. Díaz-Agudo, B., González-Calero, P.A.: Classification based retrieval using formal concept analysis. In: Aha, D.W., Watson, I. (eds.) ICCBR 2001. LNCS (LNAI), vol. 2080, pp. 173–188. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-44593-5_13

    Chapter  MATH  Google Scholar 

  8. Díaz-Agudo, B., González-Calero, P.A.: Formal concept analysis as a support technique for CBR. Knowl.-Based Syst. 14(3–4), 163–171 (2001)

    Google Scholar 

  9. Doyle, D., Cunningham, P., Bridge, D.G., Rahman, Y.: Explanation oriented retrieval. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 157–168. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8_13

    Chapter  Google Scholar 

  10. Doyle, D., Tsymbal, A., Cunningham, P.: A review of explanation and explanation in case-based reasoning (2019)

    Google Scholar 

  11. Ganter, B., Wille, R.: Formal Concept Analysis: Mathematical Foundations. Springer, Heidelberg (2012)

    MATH  Google Scholar 

  12. Gedikli, F., Jannach, D., Ge, M.: How should I explain? A comparison of different explanation types for recommender systems. Int. J. Hum Comput Stud. 72(4), 367–382 (2014)

    Article  Google Scholar 

  13. Gunning, D.: Darpa’s explainable artificial intelligence (XAI) program. In: 24th IUI, Marina del Ray, CA, USA (2019)

    Google Scholar 

  14. Harper, F.M., Konstan, J.A.: The movielens datasets: History and context. ACM Trans. Interact. Intell. Syst. 5(4), 19:1–19:19 (2015)

    Article  Google Scholar 

  15. Leake, D.B., McSherry, D.: Introduction to the special issue on explanation in case-based reasoning. Artif. Intell. Rev. 24(2), 103–108 (2005)

    Article  Google Scholar 

  16. Lee, O., Jung, J.J.: Explainable movie recommendation systems by using story-based similarity. In: 23rd ACM IUI, Tokyo, Japan (2018)

    Google Scholar 

  17. Maximini, R., Freßmann, A., Schaaf, M.: Explanation service for complex CBR applications. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 302–316. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8_23

    Chapter  Google Scholar 

  18. McSherry, D.: Explanation in recommender systems. Artif. Intell. Rev. 24(2), 179–197 (2005)

    Article  Google Scholar 

  19. Muhammad, K., Lawlor, A., Smyth, B.: A multi-domain analysis of explanation-based recommendation using user-generated reviews. In: 31st FLAIRS, Melbourne, USA, pp. 474–477 (2018)

    Google Scholar 

  20. Pu, P., Chen, L.: Trust-inspiring explanation interfaces for recommender systems. Knowl.-Based Syst. 20(6), 542–556 (2007)

    Article  Google Scholar 

  21. Schank, R.C., Kass, A., Riesbeck, C.K.: Inside Case-Based Explanation. Psychology Press (2014)

    Google Scholar 

  22. Roth-Berghofer, T.R.: Explanations and case-based reasoning: foundational issues. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 389–403. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-28631-8_29

    Chapter  Google Scholar 

  23. Singh, P.K., Aswani Kumar, C., Gani, A.: A comprehensive survey on formal concept analysis, its research trends and applications. Int. J. Appl. Math. Comput. Sci. 26(2), 495–516 (2016)

    Article  MathSciNet  Google Scholar 

  24. Sørmo, F., Cassens, J., Aamodt, A.: Explanation in case-based reasoning-perspectives and goals. Artif. Intell. Rev. 24(2), 109–143 (2005)

    Article  Google Scholar 

  25. Tintarev, N., Masthoff, J.: Explaining recommendations: design and evaluation. In: Ricci, F., Rokach, L., Shapira, B. (eds.) Recommender Systems Handbook, pp. 353–382. Springer, Boston, MA (2015). https://doi.org/10.1007/978-1-4899-7637-6_10

    Chapter  Google Scholar 

  26. Weber, R.O., Johs, A.J., Li, J., Huang, K.: Investigating textual case-based XAI. In: Cox, M.T., Funk, P., Begum, S. (eds.) ICCBR 2018. LNCS (LNAI), vol. 11156, pp. 431–447. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-01081-2_29

    Chapter  Google Scholar 

  27. Wille, R.: Restructuring lattice theory: an approach based on hierarchies of concepts. In: Rival, I. (ed.) Ordered Sets, pp. 445–470. Springer, Dordrecht (1982). https://doi.org/10.1007/978-94-009-7798-3_15

    Chapter  Google Scholar 

  28. Zanker, M., Ninaus, D.: Knowledgeable explanations for recommender systems, vol. 1, pp. 657–660 (2010)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Software Engineering and Artificial Intelligence, Universidad Complutense de Madrid, Madrid, Spain

    Belen Diaz-Agudo, Marta Caro-Martinez, Juan A. Recio-Garcia, Jose Jorro-Aragoneses & Guillermo Jimenez-Diaz

Authors
  1. Belen Diaz-Agudo
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  2. Marta Caro-Martinez
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  3. Juan A. Recio-Garcia
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  4. Jose Jorro-Aragoneses
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  5. Guillermo Jimenez-Diaz
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Corresponding author

Correspondence to Belen Diaz-Agudo .

Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, Trondheim, Norway

    Kerstin Bach

  2. Ohio University, Athens, OH, USA

    Cindy Marling

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Diaz-Agudo, B., Caro-Martinez, M., Recio-Garcia, J.A., Jorro-Aragoneses, J., Jimenez-Diaz, G. (2019). Explanation of Recommenders Using Formal Concept Analysis. In: Bach, K., Marling, C. (eds) Case-Based Reasoning Research and Development. ICCBR 2019. Lecture Notes in Computer Science(), vol 11680. Springer, Cham. https://doi.org/10.1007/978-3-030-29249-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-29249-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29248-5

  • Online ISBN: 978-3-030-29249-2

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