2528 C Porcel et aL/ Expert Systems with Applications 36(2009)12520-12528 EE Zzy Movielens.Movierecommendations<http://movielens.umn.edu/log Pazzani, M. (1999). A framework for collaborative, content-based and demographic 232.3 errera-Viedma, E(2009). A recommender urnal of the American Society for Informatio 57(4).538-54 ith Applications, 36, 5173-5183. Herrera-Viedma, E,& Peis, E(2003). Evaluating the informative quality of Quiroga, L. M.,& Mostafa, J.(2002). An experiment in building profiles in ocuments in SGML-formaf nformation Hsu, M. H (2008) A persor ing and Management, 39(2). 233-249 mender system for ESL Reisnick, P,& Varian, H. R(1 recommender Systems. Special Issue of udents Expert Systems with Applications, 34, 683-688 ommunications of the ACM, 40(3).56-59 Korfhage, R.R. (1997) Information Storage and RetrievaL New York: Wiley Computer Renda, M. E,& Straccia, U.(2005) A personalized collaborative digital library Lekakos, G,& Giaglis, G. M.(2006). Improving the prediction accuracy of 4 td development in digital lb pp.158-167) sunc.edu march/digital_library_R_and _D. html>. Accessed April 200 Papadopulo Manolopoulos, Y. (2008). Mata, F, Martinez, L,& dma, E(2009). An adaptive consens Collaborative recommender syste ng effectiveness and efficiency Morales del Castillo, JM Peis, E, Moreno, J M.& Herrera-Viedma, E(in press). D- Zadeh, L A (1975). The concept of a lines. Soft Computing. 11,631-639 Yager, RR(2007). Centered oWA operat Fussion: A semantic SDI service for the research community in digital libraries. formation Research. 975). The concept of a linguistic variable and its Morales del Castillo, J. M, Pedraza-Jimenez, R, Ruiz, AA, Peis, E,& Herrera- easoning. Part Il Information Sciences, 8, 301-357: Zadeh, L A(1975) The Viedma, E(2009). A semantic model of selective dissemination of information ncept of a linguistic variable and its applications to approximate reasoning. for digital libraries. information Technology and Libraries, 28(1) 22-31 Part llL Information Sciences, 9, 43-80linguistic preference relations. IEEE Transactions on Fuzzy Systems, 13(5), 644–658. Herrera-Viedma, E., Pasi, G., López-Herrera, A. G., & Porcel, C. (2006). Evaluating the information quality of web sites: A methodology based on fuzzy computing with words. Journal of the American Society for Information Science and Technology, 57(4), 538–549. Herrera-Viedma, E., & Peis, E. (2003). Evaluating the informative quality of documents in SGML-format using fuzzy linguistic techniques based on computing with words. Information Processing and Management, 39(2), 233–249. Hsu, M. H. (2008). A personalized English learning recommender system for ESL students. Expert Systems with Applications, 34, 683–688. Korfhage, R. R. (1997). Information Storage and Retrieval. New York: Wiley Computer Publishing. Lekakos, G., & Giaglis, G. M. (2006). Improving the prediction accuracy of recommendation algorithms: Approaches anchores on human factors. Interacting with Computers, 18, 410–431. Marchionini, G. (2009). Research and development in digital libraries. <http:// ils.unc.edu/march/digital_library_R_and_D.html>. Accessed April 2009. Mata, F., Martínez, L., & Herrera-Viedma, E. (2009). An adaptive consensus support model for group decision making problems in a multi-granular fuzzy linguistic context. IEEE Transactions on Fuzzy Systems, 17(2), 279–290. Morales del Castillo, J. M., Peis, E., Moreno, J. M., & Herrera-Viedma, E. (in press). D￾Fussion: A semantic SDI service for the research community in digital libraries. Information Research. Morales del Castillo, J. M., Pedraza-Jiménez, R., Ruíz, A. A., Peis, E., & Herrera￾Viedma, E. (2009). A semantic model of selective dissemination of information for digital libraries. Information Technology and Libraries, 28(1), 22–31. Movielens. Movie recommendations. <http://movielens.umn.edu/login>. Pazzani, M. (1999). A framework for collaborative, content-based and demographic filtering. AI Review, 13(5/6), 393–408. Porcel, C., López-Herrera, A. G., & Herrera-Viedma, E. (2009). A recommender system for research resources based on fuzzy linguistic modeling. Expert Systems with Applications, 36, 5173–5183. Quiroga, L. M., & Mostafa, J. (2002). An experiment in building profiles in information filtering: the role of context of user relevance feedback. Information Processing and Management, 38, 671–694. Reisnick, P., & Varian, H. R. (1997). Recommender Systems. Special Issue of Communications of the ACM, 40(3), 56–59. Renda, M. E., & Straccia, U. (2005). A personalized collaborative digital library environment: A model and an application. Information Processing and Management, 41, 5–21. Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2000). Analysis of recommendation algorithms for e-commerce. In Proceedings of ACM e-commerce 2000 conference (pp. 158–167). Symeonidis, P., Nanopoulos, A., Papadopoulos, A. N., & Manolopoulos, Y. (2008). Collaborative recommender systems: Combining effectiveness and efficiency. Expert Systems with Applications, 34, 2995–3013. Yager, R. R. (2007). Centered OWA operators. Soft Computing, 11, 631–639. Zadeh, L. A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Part I. Information Sciences, 8, 199–249; Zadeh, L. A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Part II. Information Sciences, 8, 301–357; Zadeh, L. A. (1975). The concept of a linguistic variable and its applications to approximate reasoning. Part III. Information Sciences, 9, 43–80. 12528 C. Porcel et al. / Expert Systems with Applications 36 (2009) 12520–12528