Context-aware Recommendation using Fuzzy Formal Concept Analysis

Jose Luis Leiva, Manuel Enciso, Carlos Rossi, Pablo Cordero, Ángel Mora, Antonio Guevara


Most of the recommender systems are content-based: they provide the user a subset of items close to his interest by using the item features. In real recommender systems, the main problem is the big amount of items to be treated. In this work we propose to incorporate context information in a uniform way. We use fuzzy logic and formal concept analysis as a framework to combine context information and content-based recommender systems. Concretely, we specify the content by using fuzzy relations, the context by using fuzzy implications and Simplification Logic to develop an intelligent and linear pre-filtering process. We illustrate this method with an application to the tourism sector.


  1. Adomavicius, G. and Tuzhilin, A. (2005). Towards the next generation of recommender systems: A survey of the state of the art and possible extensions. IEEE Transactions on Knowledge and Data Engineering archive, 17(6):734-749.
  2. Adomavicius, G. and Tuzhilin, A. (2011). Context-aware recommender systems. In Recommender Systems Handbook, pages 217-253.
  3. Adomavicius, G., Tuzhilin, A., Berkovsky, S., Luca, E. W. D., and Said, A. (2010). Context-awareness in recommender systems: research workshop and movie recommendation challenge. In RecSys, pages 385- 386.
  4. Armstrong, W. W. (1974). Dependency structures of data base relationships. In IFIP Congress, pages 580-583.
  5. Bazire, M. and Brézillon, P. (2005). Understanding context before using it. In CONTEXT, pages 29-40.
  6. Belohlavek, R. (1999). Fuzzy Galois connections. Mathematical Logic Quarterly, 45(4):497-504.
  7. Belohlavek, R., Cordero, P., Enciso, M., Mora, A., and Vychodil, V. (2012). An efficient reasoning method for dependencies over similarity and ordinal data. In Torra, V., Narukawa, Y., L ópez, B., and Villaret, M., editors, Modeling Decisions for Artificial Intelligence, volume 7647 of Lecture Notes in Computer Science, pages 408-419. Springer Berlin Heidelberg.
  8. Bertet, K. and Monjardet, B. (2010). The multiple facets of the canonical direct unit implicational basis. Theor. Comput. Sci., 411(22-24):2155-2166.
  9. Dey, A. and Abowd, G.D.and Salber, D. (2001). A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. HumanComputer Interaction, 16(2):97-166.
  10. du Boucher-Ryan, P. and Bridge, D. (2006). Collaborative recommending using formal concept analysis. Knowledge-Based Systems, 19:309-315.
  11. Ganter, B. and Wille, R. (1999). Formal Concept Analysis. Mathematical Foundations. Springer Verlag.
  12. Hájek, P. (2001). On very true. Fuzzy Sets and Systems, 124(3):329-333.
  13. Leiva, J. L., Guevara, A., and Rossi, C. (2012). Sistemas de recomendación para realidad aumentada en un sistema integral de gestión de destinos. Revista de Análisis turístico, 14:69-81.
  14. Li, X. and Murata, T. (2010). A knowledge-based recommendation model utilizing formal concept analysis and association. In 2nd International Conference on Computer and Automation Engineering (ICCAE), 2010, volume 4, pages 221- 226.
  15. Lymberopoulos, D., Zhao, P., König, A. C., Berberich, K., and Liu, J. (2011). Location-aware click prediction in mobile local search. In CIKM, pages 413-422.
  16. Wille, R. (1982). Restructuring lattice theory: an approach based on hierarchies of concepts. Ordered Sets, pages 445-470.
  17. Zenebe, A. and Norcio, A. F. (2009). Representation, similarity measures and aggregation methods using fuzzy sets for content-based recommender systems. Fuzzy Sets and Systems, 160:76-94.

Paper Citation

in Harvard Style

Luis Leiva J., Enciso M., Rossi C., Cordero P., Mora Á. and Guevara A. (2013). Context-aware Recommendation using Fuzzy Formal Concept Analysis . In Proceedings of the 8th International Joint Conference on Software Technologies - Volume 1: ICSOFT-PT, (ICSOFT 2013) ISBN 978-989-8565-68-6, pages 617-623. DOI: 10.5220/0004594406170623

in Bibtex Style

author={Jose Luis Leiva and Manuel Enciso and Carlos Rossi and Pablo Cordero and Ángel Mora and Antonio Guevara},
title={Context-aware Recommendation using Fuzzy Formal Concept Analysis},
booktitle={Proceedings of the 8th International Joint Conference on Software Technologies - Volume 1: ICSOFT-PT, (ICSOFT 2013)},

in EndNote Style

JO - Proceedings of the 8th International Joint Conference on Software Technologies - Volume 1: ICSOFT-PT, (ICSOFT 2013)
TI - Context-aware Recommendation using Fuzzy Formal Concept Analysis
SN - 978-989-8565-68-6
AU - Luis Leiva J.
AU - Enciso M.
AU - Rossi C.
AU - Cordero P.
AU - Mora Á.
AU - Guevara A.
PY - 2013
SP - 617
EP - 623
DO - 10.5220/0004594406170623