This paper presents Dietorecs, a novel case-based travel planning recommender system. Dietorecs has been designed by incorporating a human decision model that stresses individual differences in decision styles. Dietorecs supports decision styles by means of an adaptive behavior which is learned exploiting a case base of recommendation sessions that are stored by the systems. Users can enter the system through three main functional doors that fit groups of decision styles, but they can eventually switch the type of support required. The dialogue (question) is personalized using both the user model (cases) and statistics over the data available in the virtual catalogues provided by two DMOs
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Titolo: | DIETORECS: Travel Advisory for Multiple Decision Styles |
Autori: | |
Data di pubblicazione: | 2003 |
Abstract: | This paper presents Dietorecs, a novel case-based travel planning recommender system. Dietorecs has been designed by incorporating a human decision model that stresses individual differences in decision styles. Dietorecs supports decision styles by means of an adaptive behavior which is learned exploiting a case base of recommendation sessions that are stored by the systems. Users can enter the system through three main functional doors that fit groups of decision styles, but they can eventually switch the type of support required. The dialogue (question) is personalized using both the user model (cases) and statistics over the data available in the virtual catalogues provided by two DMOs |
Handle: | http://hdl.handle.net/11582/725 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |