A hierarchical multi-criteria sorting approach for recommender systems

Abstract

Classification problems refer to the assignment of alternatives to predefined categories. In this work we focus on ordered classification, called sorting, in which the predefined categories indicate several degrees of interest or suitability of alternatives for a certain user. The assignment of alternatives is based on multiple conflicting criteria. This multi-criteria sorting approach is specially interesting for recommender systems aimed at finding the most suitable alternatives for each user. First, we study the ELECTRE-TRI-B sorting method, which follows the outranking approach based on comparing the evaluations of alternatives with the profile limits separating the categories. The complexity of some recommenders systems requires the extension of the classical ELECTRE-TRI-B method to manage a taxonomical organization of the set of criteria. In this paper we consider a set of criteria in the form of a hierarchy. The intermediate criteria in such a hierarchy correspond to different aspects of the recommendation procedure, such as content, context or cost. At each of these criteria, a sorting problem must be solved. Therefore, we propose extending Luis Del Vasto-Terrientes J Intell Inf Syst ELECTRE-TRI-B to handle assignments of alternatives on several levels of the hierarchy. A hierarchical procedure for sorting is proposed, called ELECTRE-TRI-B-H. Secondly, the paper explains the integration of ELECTRE-TRI-B-H into a recommender system of touristic activities related to wine, called GoEno-Tur. This system is developed for the region of Tarragona, Catalonia (Spain), which is a well-recognized area of wine and cava production.

Design and evaluation of planning and mathematical models for generating learning paths

“…3 Finally, we need metrics in online tutoring systems to assess the utilities of learning paths to choose those that better adapt to student progress. 16,34,36,37 Assembling learning objects is the most difficult task toward generating rich learning experiences for students. 6,38 There is work that selects learning contents to construct learning sequences based on task difficulty, 31 and priorities.…”

“…Planning for fulfillment of competencies is important, but sometimes, teachers are more interested in the partial progress of learning objectives . Finally, we need metrics in online tutoring systems to assess the utilities of learning paths to choose those that better adapt to student progress …”