The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Intrigue: Personalized recommendation of tourist attractions for desktop and hand held devices
Open accessAbstract
This paper presents INTRIGUE, a prototype tourist-information server that presents information about the area around Turin City, Italy, on desktop and hand held devices.This system recommends sightseeing destinations and itineraries by taking into account the preferences of heterogeneous tourist groups (such as families with children or the elderly) and explains the recommendations by addressing the group members' requirements. Moreover, the system provides an interactive agenda for scheduling the tour. The services offered by INTRIGUE rely on user modeling and adaptive hypermedia techniques; furthermore, XML-based technologies support the generation of the user interface and its adaptation to Web browsers and WAP minibrowsers.
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Cites
Brusilovsky, P. (2001) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1011143116306 · Cited by 2,057
Explaining collaborative filtering recommendations
Herlocker, J. L., Konstan, J. A., & Riedl, J. (2000) · Proceedings of the 2000 ACM conference on Computer supported cooperative work · doi:10.1145/358916.358995 · Cited by 1,731
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Adomavicius, G., & Tuzhilin, A. (2011) · Recommender Systems Handbook · doi:10.1007/978-0-387-85820-3_7 · Cited by 1,102
'It's Reducing a Human Being to a Percentage': Perceptions of Justice in Algorithmic Decisions
Binns, R., Van Kleek, M., Veale, M., Lyngs, U., Zhao, J., & Shadbolt, N. (2018) · Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3173574.3173951 · Cited by 691
“rom the model’s training data which most closely resemble the output in question [12,54], while ‘demographic’ explanations provide statistics on the outcome classes for relevant demographic variables [2]. While these different explanation stylessuggest promising ways to explain the outputs of any classifier, explanati…”
BackgroundPersonalization in cultural heritage: the road travelled and the one ahead
Ardissono, L., Kuflik, T., & Petrelli, D. (2012) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-011-9104-x · Cited by 257
Self-citationUnderstanding and managing customer relational benefits in services: a meta-analysis
Gremler, D. D., Van Vaerenbergh, Y., Brüggen, E. C., & Gwinner, K. P. (2020) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-019-00701-6 · Cited by 148
Metadata
- Authors
- Ardissono, L., Goy, A., Petrone, G., Segnan, M., & Torasso, P.
- Venue
- Applied Artificial Intelligence
- Publisher
- Informa UK Limited
- Published
- 2003-09
- Volume
- 17
- Issue
- 8-9
- Pages
- 687-714
- ISSN
- 0883-9514 (ISSN-L)
- 1087-6545
- OpenAlex
- W2059903060
- Cited by
- 384
- References
- 2
- FWCI
- 15.87
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Ardissono, L., Goy, A., Petrone, G., Segnan, M., & Torasso, P. (2003). Intrigue: Personalized recommendation of tourist attractions for desktop and hand held devices. Applied Artificial Intelligence. https://doi.org/10.1080/713827254
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