Personalized e-commerce recommendations

P. Markellou, I. Mousourouli, S. Sirmakessis, A. Tsakalidis
2005 IEEE International Conference on e-Business Engineering (ICEBE'05)  
Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today's e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as web mining, semantics, artificial intelligence, user modeling and profiling, etc. setting up a successful recommendation system is not a trivial or straightforward task. This paper argues that by monitoring,
more » ... analyzing and understanding the behavior of customers, their demographics, opinions, preferences and history, as well as taking into consideration the specific e-shop ontology and by applying web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users' interaction, increase its usability, convert users to buyers, retain current customers and establish longterm and loyal one-to-one relationships.
doi:10.1109/icebe.2005.95 dblp:conf/icebe/MarkellouMST05 fatcat:p2jqxwf6irc6ddrhf3cysvw2oy