1,721,629 research outputs found
Replication Data for: Evaluating Explainable Social Choice-based Aggregation Strategies for Group Recommendations with Internal Evaluators
No full textIn this project, we perform a user study to evaluate the effectiveness of Social Choice-Based Explanations for Group Recommender Systems using internal evaluators (i.e., group members evaluate the recommendations provided for the group), in different complex scenarios, whose complexity is determined by the number of group members, the number of possible items, and the diversity between group members' preferences. For additional details and material refer to the OSF project: https://osf.io/sj76m
UM XAI Explainable - GRS Impact of scenario complexity
No full textIn this project, we perform a user study to evaluate the effectiveness of Social Choice-Based Explanations for Group Recommender Systems in different complex scenarios, whose complexity is determined by the number of group members, the number of possible items, and the diversity between group members' preferences. The collected answer, properly anonymized, are collected in this dataset. Information on the experiment are available in the preregistration document, which can be accessed, together with the R script for reproducing the performed statistical analyses, at the link: https://osf.io/3dcht
Towards a Collaborative Filtering Framework for Recommendation in Museums: From Preference Elicitation to Group's Visits
No full textRecommendation systems based on collaborative filtering methods can be exploited in the context of providing personalized artworks tours within a museum. However, in order to be effectively used, several problems have to be addressed: user preferences are not expressed as rating, items to be suggested are located in a physical space, and users may be in a group. In this work, we present a general framework that, by using the Matrix Factorization (MF) approach and a graph representation of a museum, addresses the problem of generating and then recommending an artworks sequence for a group of visitors within a museum. To reach a high-quality initial personalization, the recommendation system uses a simple, but efficient, elicitation method that is inspired by the MF approach. Moreover, the proposed approach considers the individual or the aggregated artworks’ ratings to build up a solution that takes into account the physical location of the artworks
Conflict resolution profiles and agent negotiation for group recommendations
No full textThe pervasive use of web technologies and online cooperation tools is posing new challenges in the design of recommender systems, requiring now a rapid move from individual to group recommendations. In this paper, a multi-agent system to provide support to small groups of users in their decisionmaking process is presented. In detail, the addressed problem is to find a common solution for a group, represented by a set of activities in the touristic domain, among a huge set of possible alternatives, that meets the preferences of each member. The proposed system uses an automatic negotiation process that incrementally builds a candidate solution for the whole group according to the individual lists of each group member. Since the negotiation mechanism involves the real users to take part in the decision-making process, the proposed approach tries to limit the agreement search space during the negotiation process in order to minimize the user direct intervention. The proposed solution relies on negotiating agents that simulate the users' behavior while trading by using different conflict resolution styles, obtained by applying the Thomas Kilmann model. The results obtained with both simulated and real users' behavior show that the proposed system achieves a high probability of success, finding a shared solution, in most cases, in a relatively small number of rounds of negotiation. In addition, end users were satisfied with the received recommendations
L'innovazione tra creatività e sostenibilità
No full textIl contributo intende tracciare un percorso interpretativo del processo di innovazione nelle organizzazioni inquadrandolo tra attività creative del pensiero e scelte valoriali ispirate ad una visione di sostenibilità.
Il processo creativo così ispirato si può realizzare a livello di individui e di organizzazioni nonchè di network di organizzazioni secondo una logica di combinazione creativa della varietà
Dominance Weighted Social Choice Functions for Group Recommendations
Full text linkIn travel domains, decision support systems provide support to tourists in the planning of their vacation. In particular, when the number of possible Points of Interest (POI) to visit is large, the system should help tourists providing recommendations on the POI that could be more interesting for them. Since traveling is, usually, an activity that involves small groups of people, the system should take simultaneously into account the preferences of each group's member. At the same time, it also should model possible intra-group relationships, which can have an impact in the group decision-making process. In this paper, we model this problem as a multi-agent aggregation of preferences by using weighted social choice functions, whereas such weights are automatically evaluated by analyzing the interactions of the group's members on Online Social Networks.</pre
Modeling the Changing of the Individual Satisfaction in a Group Context: A Study on Two Sized Groups
No full text- …
