Abstract
In this paper, we present a Context Aware Thai Tourism Recommender System (CAT-TOURS) that applies a complex Naïve Bayes Model with boundary values, tourism ontology for Thailand and a temporal ontology to support decision making in tourism. Promising results are presented in the form of precision, recall and F measure for Websites related to Thailand’s tourism industry. We compare the results with those gained with Latent Semantic Indexing (LSI).
This research was guided by the following aims: (1) find a simple method to classify Thai tourism Web documents that contain information on more than one topic, and (2) take into account time constraints in the process of making recommendations.
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Namahoot, C.S., Brückner, M., Panawong, N. (2015). Context-Aware Tourism Recommender System Using Temporal Ontology and Naïve Bayes. In: Unger, H., Meesad, P., Boonkrong, S. (eds) Recent Advances in Information and Communication Technology 2015. Advances in Intelligent Systems and Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-19024-2_19
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DOI: https://doi.org/10.1007/978-3-319-19024-2_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19023-5
Online ISBN: 978-3-319-19024-2
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