Abstract
Nowadays, there is a constant need for personalization in recommender systems. Thus, they try to bring it by making suggestion and providing information about items available. There are numerous options of methods to be employed in recommender systems. However, they still suffer from critical limitations and drawbacks. Therefore, current recommender techniques try to minimize the affects of such drawbacks. In this work we describe two different recommender methodologies proposed. To do so, we implemented such methodologies in a real recommender system for tourism. Afterwards, we analyzed and compared the recommendation given by both methodologies in order to find out if they are effective and able to deal with common drawbacks.
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Lucas, J.P., da Silva Coelho, B.E., García, M.N.M., de Almeida Figueiredo, A.M., Martins, C.L. (2011). Applying Recommender Methodologies in Tourism Sector. In: Pérez, J.B., et al. Highlights in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 89. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19917-2_13
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DOI: https://doi.org/10.1007/978-3-642-19917-2_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19916-5
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