Applying Recommender Methodologies in Tourism Sector

Autor:	Ana Maria de Almeida Figueiredo, Bruno E. da Silva Coelho, Joel Pinho Lucas, María N. Moreno García, Constantino Martins
Rok vydání:	2011
Předmět:	Order (exchange) Computer science Recommender system Data science Tourism Personalization
Zdroj:	Advances in Intelligent and Soft Computing ISBN: 9783642199165 PAAMS (Special Sessions)
DOI:	10.1007/978-3-642-19917-2_13
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::2722720e9bc3028b7f20b2b2c8121319 https://doi.org/10.1007/978-3-642-19917-2_13 Zobrazit plný text záznamu