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The formation of groups is an ordinary event in ourroutines. For example, people used to lunch, travel, or hang out in groups. Conversely, getting a consensus over an item may be difficult for some groups as the number of digital information increases. Group Recommender Systems (GRS) rise to assist in this task, as they filter which items may be more relevant to the group. Although there are consensus...
Many computational techniques have been proposed by social networks to analyze the users' behaviors to recommend relevant content for them. Social networks generate a huge volume of information, which users cannot consume, generating a problem known as information overload. This way, filtering relevant information to help users with this problem becomes necessary. Social networks have many available...
Recommendation strategies are used in several contexts in order to bring potential users closer to products with a strong probability of interest. When recomendations focus on niche items, they are called recommendations in the long tail. In these cases, they also look for less popular items and try to find your target custumer, niche market. This paper proposes a long tail recommendation approach...
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