Introducing learning and adaptivity into web‐based recommender systems for tourism and leisure services

Travel counseling and recommender systems on the Internet have not yet become smart enough to fulfill the elementary functions a fastidious consumer may expect. The EU‐funded project named DieToRecs (http://dietorecs.itc.it/) aims at improving recommender system functionality by incorporating relevant findings from tourist behavior research. The computational intelligence needed to optimize the user‐system encounter greatly depends on how far the user has advanced in his travel decision process. This report elaborates the levels of counseling intelligence, explores the basic marketing paradigm of matching the products/services desired and offered, and ponders on the consequences for devising a recommender or counseling system capable of learning.