Adomavicius, G., Manouselis, N., & Kwon, Y. (2011). Multi-Criteria Recommender Systems. In Ricci, F., Rokach, L., Shapira, B, & Kantor, P. B. (Eds.), Recommender Systems Handbook, (pp. 769–803). US: Springer.
Chapter
Google Scholar
Arondel, C., & Girardin, P. (2000). Sorting cropping systems on the basis of their impact on groundwater quality. European Journal of Operational Research, 127, 467–482.
Article
MATH
Google Scholar
Bana e Costa, C., & Vansnick, J. (1999). The MACBETH Approach: Basic Ideas, Software, and an Application. In Meskens, N., & Roubens, M. (Eds.), Advances in Decision Analysis, Mathematical Modelling: Theory and Applications, vol 4, (pp. 131–157). Netherlands: Springer.
Chapter
Google Scholar
Borràs, J., Moreno, A., Valls, A., Ferré, M., Ciurana, E., Salvat, J., Russo, A., & Anton-Clavé, S. (2012a). Uso de técnicas de inteligencia artificial para hacer recomendaciones enoturística personalizadas en la provincia de tarragona. In IX Congreso Nacional de Turismo y Tecnologías de la Información y las Comunicaciones (TURITEC) (pp. 217–230).
Borràs, J., Valls, A., Moreno, A., & Isern, D. (2012b). Ontology-based management of uncertain preferences in user profiles. In 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems (IPMU) (pp. 127–136).
Borràs, J., Moreno, A., & Valls, A. (2014). Intelligent tourism recommender systems: A survey. Expert Systems with Applications, 41, 7370–7389.
Article
Google Scholar
Brito, A., de Almeida, A., & Mota, C. (2010). A multicriteria model for risk sorting of natural gas pipelines based on ELECTRE TRI integrating Utility Theory. European Journal of Operational Research, 200, 812–821.
Article
MATH
Google Scholar
Cailloux, O., Meyer, P., & Mousseau, V. (2012). Eliciting Electre Tri category limits for a group of decision makers. European Journal of Operational Research, 223, 133–140.
MathSciNet
Article
MATH
Google Scholar
Cailloux, O., Mayag, B., Meyer, P., & Mousseau, V. (2013). Operational tools to build a multicriteria territorial risk scale with multiple stakeholders. Reliability Engineering & System Safety, 120, 88–97.
Article
Google Scholar
Chen, S., Liu, J., Wang, H., Xu, Y., & Augusto, J. (2014). A linguistic multi-criteria decision making approach based on logical reasoning. Information Sciences, 258, 266–276.
MathSciNet
Article
MATH
Google Scholar
Cloquell-Ballester, V., Monterde-Díaz, R., Cloquell-Ballester, V., & Santamarina-Siurana, M. (2007). Systematic comparative and sensitivity analyses of additive and outranking techniques for supporting impact significance assessments. Environmental Impact Assessment Review, 27, 62–83.
Article
Google Scholar
Corrente, S., Greco, S., Kadzinski, M., & Slowinski, R. (2013). Robust ordinal regression in preference learning and ranking. Machine Learning, 93(2–3), 381–422.
MathSciNet
Article
MATH
Google Scholar
De Gemmis, M., Iaquinta, L., Lops, P., Musto, C., Narducci, F., & Semeraro, G. (2009). Preference learning in recommender systems. In Preference Learning (PL-09) ECML/PKDD-09 Workshop.
Deuk Hee, P., Hyea Kyeong, K., Il Young, C., & Jae Kyeong, K. (2012). A literature review and classification of recommender systems research. Expert Systems with Applications, 39(11), 10,059–10,072.
Article
Google Scholar
Doumpos, M., & Grigoroundis, E. (2013). Multicriteria Decision Aid and Artificial Intelligence. Wiley.
Doumpos, M., & Zopounidis, C. (2011). Preference disaggregation and statistical learning for multicriteria decision support: A review. European Journal of Operational Research, 209(3), 203–214.
MathSciNet
Article
MATH
Google Scholar
Ehrgott, M., Figueira, J., & Greco, S. (2010). Trends in Multiple Criteria Decision Analysis. Berlin: Springer.
Book
MATH
Google Scholar
Fenza, G., Fischetti, E., Fumo, D., & Loia, V. (2011). A hybrid context aware system for tourist guidance based on collaborative filtering. In Fuzzy Systems (FUZZ), 2011 IEEE International Conference (pp. 131–138).
Figueira, J., & Roy, B. (2002). Determining the weights of criteria in the electre type methods with a revised simos’ procedure. European Journal of Operational Research, 139(2), 317–326.
MathSciNet
Article
MATH
Google Scholar
Gavalas, D., Konstantopoulos, C., Mastakas, K., & Pantziou, G. (2014). Mobile recommender systems in tourism. Journal of Network and Computer Applications, 39, 319–333.
Article
Google Scholar
Grabisch, M., Kojadinovic, I., & Meyer, P. (2008). A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package. European Journal of Operational Research, 186(2), 766–785.
MathSciNet
Article
MATH
Google Scholar
Hdioud, F., Frikh B., & Ouhbi, B. (2013). Multi-criteria recommender systems based on multi-attribute decision making. In Proceedings of International Conference on Information Integration and Web-based Applications & Services, ACM, New York, NY, USA, IIWAS ’13 (pp. 203:203–203:210).
Huang, S. (2011). Designing utility-based recommender systems for e-commerce: Evaluation of preference-elicitation methods. Electronic Commerce Research and Applications, 10, 398–407.
Article
Google Scholar
Lakiotaki, K., Matsatsinis, N., & Tsoukias, A. (2011). Multicriteria User Modeling in Recommender Systems. IEEE Intelligent Systems, 26(2), 64–76.
Article
Google Scholar
Law, R., Qi, S., & Buhalis, D. (2010). Progress in tourism management: A review of website evaluation in tourism research. Tourism Management, 31(3), 297–313.
Article
Google Scholar
Li, D., Liu, C., & Gan, W. (2009). A new cognitive model: Cloud model. International Journal of Intelligent Systems, 24, 357–375.
Article
MATH
Google Scholar
Liu, L., Mehandjiev, N., & Xu, D. (2011). Multi-criteria Service Recommendation Based on User Criteria Preferences. In Proceedings of the Fifth ACM Conference on Recommender Systems, ACM, New York, NY, USA, RecSys ’11 (pp. 77–84).
Lops, P., De Gemmis, M., Semeraro, G., Musto, C., & Narducci, F. (2013). Content-based and collaborative techniques for tag recommendation: An empirical evaluation. Journal of Intelligent Information Systems, 40, 41–61.
Article
Google Scholar
Mandl, M., Felfernig, A., Teppan, E., & Schubert, M. (2011). Consumer decision making in knowledge-based recommendation. Journal of Intelligent Information Systems, 37, 1–22.
Article
Google Scholar
Manjeevan, S., Chee Peng, L., Wei Shiung, L., Einly, L., & Chu Kiong, L. (2015). Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models. Expert Systems with Applications, 42(7), 3643–3652.
Article
Google Scholar
Matsatsinis, N., Doumpos, M., & Zopounidis, C. (1997). Knowledge acquisition and representation for expert systems in the field of financial analysis. Expert Systems with Applications, 12, 247–262.
Article
Google Scholar
Mikeli, A., Sotiros, D., Apostolou, D., & Despotis, D. (2013). A multi-criteria recommender system incorporating intensity of preferences. In Information, Intelligence, Systems and Applications (IISA), 2013 Fourth International Conference on (pp. 1–6).
Moreno, A., Valls, A., Isern, D., Marin, L., & Borràs, J. (2013). SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities. Engineering Applications of Artificial Intelligence, 26, 633–651.
Article
Google Scholar
Moreno, A., Valls, A., Martínez, S., Vicient, C., Marin, L., & Mata, F. (2015). Personalised recommendations based on novel semantic similarity and clustering procedures. AI Commun, 28(1), 127–142.
MathSciNet
Google Scholar
Mousseau, V., Slowinski, R., & Zielniewicz, P. (2000). A user-oriented implementation of the ELECTRE-TRI method integrating preference elicitation support. Computers and Operations Research, 27, 757–777.
Mustajoki, J. (2012). Effects of imprecise weighting in hierarchical preference programming. European Journal of Operational Research, 218, 193–201.
MathSciNet
Article
MATH
Google Scholar
Perny, P., & Pomerol, J. (1999). Use of artificial intelligence in mcdm. In Gal, T., Stewart, T., & Hanne, T. (Eds.) Multicriteria Decision Making: Advances in MCMD Models, Algorithms, Theory, and Applications, vol (pp. 1–43).
Qiang, W.J., Peng, L., Yu Z.H., & Hong, C.X. (2014). Method of multi-criteria group decision-making based on cloud aggregation operators with linguistic information. Information Sciences, 1, 177–191.
Roy, B. (1996). Multicriteria Methodology for Decision Analysis. Dordrecht: Kluwer Academic Publishers.
Book
Google Scholar
Saaty, R. (1987). The analytic hierarchy process-what it is and how it is used. Mathematical Modelling, 9(3-5), 161–176.
MathSciNet
Article
MATH
Google Scholar
Sánchez-Lozano, J., Henggeler Antunes, C., García-Cascales, M., & Dias, L. (2014). GIS-based photovoltaic solar farms site selection using ELECTRE-TRI: Evaluating the case for Torre Pacheco, Murcia, Southeast of Spain. Renewable Energy, 66, 478–494.
Article
Google Scholar
Silva, S., Alçada-Almeida, L., & Dias, L. (2014). Biogas plants site selection integrating Multicriteria Decision Aid methods and GIS techniques: A case study in a Portuguese region. Biomass and Bioenergy, 71, 58–68.
Article
Google Scholar
Siskos, Y., Grigoroudis, E., & Matsatsinis, N. (2005). Uta methods. Multiple Criteria Decision Analysis: State of the Art Surveys, International Series in Operations Research & Management Science, vol 78, (pp. 297–334). New York: Springer.
Sobrie, O., Mousseau, V., & Pirlot, M. (2013). Learning a Majority Rule Model from Large Sets of Assignment Examples. In Perny, P., Pirlot, M., & Tsoukiàs, A. (Eds.), Algorithmic Decision Theory, Lecture Notes in Computer Science, vol 8176, (pp. 336–350). Berlin Heidelberg: Springer.
Google Scholar
Xidonas, P., Mavrotas, G., & Psarras, J. (2009). A multicriteria methodology for equity selection using financial analysis. Computers and Operations Research, 36, 3187–3203.
Article
MATH
Google Scholar
Yu, W. (1992). Electre tri : Aspects mthodologiques et manuel dutilisation. Document du LAMSADE, No.74, Universit Paris-Dauphine.
Zopounidis, C., & Doumpos, M. (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138, 229–246.
MathSciNet
Article
MATH
Google Scholar