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E-commerce has become a major application domain for recommender systems due to its business interest. These tools aim to identify the products each user may like or find useful, which can boost users' consumption. Particularly, collaborative recommender systems rely on a set of like-minded users to select the products to offer. Taking into account the expertise of the users who drive such decision...
Tourists need advice about what to do in their trips. Bearing in mind the wide adoption and influence of social technologies from Web 2.0, we propose a tourism recommender system that offers tourist packages with two features: (i) they include the attractions and activities that best match the users' preferences, which are inferred from their profiles in social networks, and (ii) these packages have...
Recommender systems have proven to be an effective response to the information overload problem, by identifying items the users may be interested in. Trust and reputation are being increasingly incorporated in collaborative recommender systems in order to improve their accuracy and reliability, using network structures in which nodes represent users and edges represent trust statements. However, current...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.