In a ubiquitous scenario, people are typically confronted with context evolution and changing inuences. This may create new needs and may condition the user perception of what is relevant information. Over the years, different approaches have been proposed to design personalized Recommender Systems (RS), but state-of-the-art approaches mostly assume a fixed representation of a user profile; the dynamicity of the user's interests (and the way of expressing them) while interacting with the environment is not considered. Aim of this work is to predict a user's preferences in the tourism domain, to provide personalized and contextaware recommendations. Therefore, we define a user profile model which expresses in a formal way the user's opinions with respect to a particular entity. In particular, the proposed approach formally models the user generated content (UGC) connected to a group of reviews (written by expert users) for each entity, and compares it with a (positive and negative) statistical language model representing the target user profile associated with that entity. The effectiveness of the approach is illustrated on a real-case scenario.

Missaoui, S., Viviani, M., Faiz, R., Pasi, G. (2017). A language modeling approach for the recommendation of tourism-related services. In Proceedings of the ACM Symposium on Applied Computing (pp.1697-1700). Association for Computing Machinery [10.1145/3019612.3019900].

A language modeling approach for the recommendation of tourism-related services

MISSAOUI, SONDESS
Primo
;
VIVIANI, MARCO
Secondo
;
PASI, GABRIELLA
Ultimo
2017

Abstract

In a ubiquitous scenario, people are typically confronted with context evolution and changing inuences. This may create new needs and may condition the user perception of what is relevant information. Over the years, different approaches have been proposed to design personalized Recommender Systems (RS), but state-of-the-art approaches mostly assume a fixed representation of a user profile; the dynamicity of the user's interests (and the way of expressing them) while interacting with the environment is not considered. Aim of this work is to predict a user's preferences in the tourism domain, to provide personalized and contextaware recommendations. Therefore, we define a user profile model which expresses in a formal way the user's opinions with respect to a particular entity. In particular, the proposed approach formally models the user generated content (UGC) connected to a group of reviews (written by expert users) for each entity, and compares it with a (positive and negative) statistical language model representing the target user profile associated with that entity. The effectiveness of the approach is illustrated on a real-case scenario.
poster + paper
Content-based filtering; Information filtering; Language models; Tourism service recommendation; User profiling;
Content-based filtering; Information filtering; Language models; Tourism service recommendation; User profiling; Software
English
32nd Annual ACM Symposium on Applied Computing, SAC 2017
2017
Proceedings of the ACM Symposium on Applied Computing
9781450344869
2017
128005
1697
1700
none
Missaoui, S., Viviani, M., Faiz, R., Pasi, G. (2017). A language modeling approach for the recommendation of tourism-related services. In Proceedings of the ACM Symposium on Applied Computing (pp.1697-1700). Association for Computing Machinery [10.1145/3019612.3019900].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/168477
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