title: Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module
creator: Lazanas, Alexis 
subject: Machine Learning
description: Diverse recommendation techniques have been already proposed and encapsulated into several e-business applications, aiming to perform a more accurate evaluation of the existing information and accordingly augment the assistance provided to the users involved. This paper reports on the development and integration of a recommendation module in an agent-based transportation transactions management system. The module is built according to a novel hybrid recommendation technique, which combines the advantages of collaborative filtering and knowledge-based approaches. The proposed technique and supporting module assist customers in considering in detail alternative transportation transactions that satisfy their requests, as well as in evaluating completed transactions. The related services are invoked through a software agent that constructs the appropriate knowledge rules and performs a synthesis of the recommendation policy.
publisher: International Journal of Computer Science Issues, IJCSI
date: 2009-08
type: Journal (Paginated)
type: PeerReviewed
format: application/pdf
identifier: http://cogprints.org/6703/1/3-24-34.pdf
identifier:   Lazanas, Alexis   (2009) Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module.  [Journal (Paginated)]     
relation: http://cogprints.org/6703/