Paper Info
Title
DG-GPR: A Decision-Guided Group Package Recommender With Hybrid Condorcet-Instant Runoff Voting.
Abstract
This paper proposes a Decision-Guided Group Package Recommender (DG-GPR) framework, which provides recommendations on dynamically defined packages of products and services. This framework is based on: (1) defining the space of alternatives; (2) eliciting the utility function for each individual decision maker; (3) estimating the group utility function; (4) using the group utility function to find an optimal recommendation alternative; (5) constructing a set of diverse recommendations which contains the optimal recommendation alternative; and (6) applying a Hybrid Condorcet-Instant Runoff Voting method from social choice theories, to refine the recommendations. A preliminary experimental study is conducted which shows that the proposed framework significantly outperforms its previous extension which in turn had previously outperformed three popular aggregation strategies.
Year
DOI
Venue
2014
10.3233/978-1-61499-399-5-317
Frontiers in Artificial Intelligence and Applications
Keywords
Field
DocType
Decision guidance,group recommender systems,decision optimization,group decision support
Data mining,Ground-penetrating radar,Computer science,Instant-runoff voting,Condorcet method
Conference
Volume
ISSN
Citations 
261
0922-6389
1
PageRank 
References 
Authors
0.35
0
2
Name
Order
Citations
PageRank
Hanan Mengash110.35
Alexander Brodsky251092.99