Discovering user preferences using Dempster–Shafer theory

This paper presents a model for discovering user preferences from item characteristics. Based on the theory of evidence, the model estimates a probability interval for an item represented by a set of features. This interval represents the item preference within a group of users and it is computed ac...

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Bibliographic Details
Published inFuzzy sets and systems Vol. 278; pp. 98 - 117
Main Authors Troiano, Luigi, Rodríguez-Muñiz, Luis J., Díaz, Irene
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.11.2015
Subjects
Belief
Dempster–Shafer theory
Lattice mining
Plausibility
Recommendation system
User preferences
Belief
Dempster–Shafer theory
User preferences
Plausibility
Lattice mining
Recommendation system
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Summary:This paper presents a model for discovering user preferences from item characteristics. Based on the theory of evidence, the model estimates a probability interval for an item represented by a set of features. This interval represents the item preference within a group of users and it is computed according to preferences expressed in the past. Additionally, a method for moving among different domains and fusing information is outlined. The issue of efficient search subsets of interest within the inclusion lattice is investigated and algorithms are presented.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2015.06.004