Paper Info
Title
Exploiting graph-theoretic tools for matching in carpooling applications.
Abstract
An automatic service to match commuting trips has been designed. Candidate carpoolers register their personal profile and a set of periodically recurring trips. The Global CarPooling Matching Service shall advise registered candidates how to combine their commuting trips by carpooling. Planned periodic trips correspond to nodes in a graph; the edges are labeled with the probability for for success while negotiating to merge two planned trips by carpooling. The probability values are calculated by a learning mechanism using on one hand the registered person and trip characteristics and on the other hand the negotiation feedback. The probability values vary over time due to repetitive execution of the learning mechanism. As a consequence, the matcher needs to cope with a dynamically changing graph both with respect to topology and edge weights. In order to evaluate the matcher performance before deployment in the real world, it will be exercised using a large scale agent based model. This paper describes both the exercising model and the matcher.
Year
DOI
Venue
2014
10.1007/s12652-013-0197-4
J. Ambient Intelligence and Humanized Computing
Keywords
Field
DocType
Graph theory, Binary matching, Agent-based modeling, Scalability, Dynamic networks, Learning
Graph theory,Graph,Software deployment,Agent-based model,Computer science,Simulation,Artificial intelligence,TRIPS architecture,Periodic graph (geometry),Machine learning,Scalability,Negotiation
Journal
Volume
Issue
ISSN
5
3
1868-5145
Citations 
PageRank 
References 
9
0.86
8
Authors
11
Name
Order
Citations
PageRank
Luk Knapen18622.42
Ansar-Ul-Haque Yasar211842.31
Sungjin Cho3366.49
Daniel Keren4931116.90
Abed Abu Dbai5121.30
Tom Bellemans67323.16
Davy Janssens723838.08
Geert Wets876667.59
Assaf Schuster92304145.56
Izchak Sharfman1025713.37
Kanishka Bhaduri1128918.96