relation: http://eprints.imtlucca.it/1494/
title: Serendipitous Fuzzy Item Recommendation with ProfileMatcher
creator: Dell’Agnello, Danilo
creator: Fanelli, Anna
creator: Mencar, Corrado
creator: Minervini, Massimo
subject: QA75 Electronic computers. Computer science
description: In this paper an approach to serendipitous item recommendation is outlined. The model used for this task is an extension of ProfileMatcher, which is based on fuzzy metadata describing both user and items to be recommended. To address the task of recommending serendipitous resources, a priori knowledge on the relations occurring among metadata values is injected in the recommendation process. This is achieved using fuzzy graphs to model similarity relations among the elements of the fuzzy sets describing the metadata. An experimentation has been carried out on the MovieLens data set to show the impact of serendipity injection in the item recommendation process.
publisher: Springer
date: 2011
type: Book Section
type: PeerReviewed
identifier:   Dell’Agnello, Danilo and Fanelli, Anna and Mencar, Corrado and Minervini, Massimo  Serendipitous Fuzzy Item Recommendation with ProfileMatcher.   In:  Fuzzy Logic and Applications.   Lecture Notes in Computer Science  (6857).  Springer, pp. 220-227.  ISBN  978-3-642-23712-6      (2011)  
relation: http://dx.doi.org/10.1007/978-3-642-23713-3_28
relation: 10.1007/978-3-642-23713-3_28