creators_name: Lazanas, Alexis type: journalp datestamp: 2009-11-14 11:32:53 lastmod: 2011-03-11 08:57:32 metadata_visibility: show title: Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module ispublished: pub subjects: comp-sci-mach-learn full_text_status: public keywords: Data mining, Knowledge Association Rules, Recommender systems, Intermodal Transportation abstract: 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. date: 2009-08 date_type: published publication: A. Lazanas, "Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module", International Journal of Computer Science Issues, IJCSI, Volume 3, pp24-34, August 2009 volume: 3 publisher: International Journal of Computer Science Issues, IJCSI refereed: TRUE citation: Lazanas, Alexis (2009) Performing Hybrid Recommendation in Intermodal Transportation – the FTMarket System’s Recommendation Module. [Journal (Paginated)] document_url: http://cogprints.org/6703/1/3-24-34.pdf