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Joint purchases are a growing business activity with benefits to both consumers and sellers. We present a system that proactively and intelligently helps identify opportunities for joint purchasing and carry out this type of transactions.
This paper presents the prediction of TV station ratings considering the user's profile of its audience, received from their settop boxes. It is based on a TV content recommender for groups that uses multidimensional classifications following the TV-Anytime approach. Two applications are presented in order to maximize ratings: an algorithm to configure the TV program schedule of a TV station, and...
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...
This paper presents a semantic search engine focused on the query construction process with semantic validation capabilities as well as a personalized natural language automatic generation from the query, and its application in the Digital TV domain.
Consumers are flooded with amounts of discount coupons, oftentimes for products that are far from their interests. This marketing custom is already rising in Internet, and it is imminent in Digital TV. But the computing capability of these media permits to alleviate this problem by means of recommender systems, very useful tools in application domains that suffer from information overload. However,...
Consumers are flooded with amounts of discount coupons, oftentimes for products that are far from their interests. This marketing custom is already rising on the Internet and is imminent in Digital TV, where the massive sending of coupons leads to their devaluation and consumer indifference. The computing capabilities of these media permit to alleviate this problem by means of recommender systems,...
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