Exploiting Regression Trees as User Models for Intent-Aware Multi-attribute Diversity

Diversity in a recommendation list has been recognized as one of the key factors to increase user’s satisfaction when interacting with a recommender system. Analogously to the modelling and exploitation of query intent in Information Retrieval adopted to improve diversity in search results, in this paper we focus on eliciting and using the profile of a user which is in turn exploited to represent her intents. The model is based on regression trees and is used to improve personalized diversification of the recommendation list in a multi-attribute setting. We tested the proposed approach and showed its effectiveness in two different domains, i.e. books and movies. Categories and Subject Descriptors H.3.3 [Information Systems]: Information Search and Retrieval Keywords Personalized diversity; Intent-aware diversification; Regression Trees

• Type: Journal
• Year: 2015
• Where: RECSYS
• Authors: Paolo Tomeo, Tommaso Di Noia, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro, Eugenio Di Sciascio
• Keywords: Control Systems, RECSYS 2015