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We examine the problem of recommending items to ad-hoc user groups. Group recommendation in collaborative rating datasets has received increased attention recently and has raised novel challenges. Different consensus functions that aggregate the ratings of group members with varying semantics ranging from least misery to pairwise disagreement, have been(More)
User data is becoming increasingly available in multiple domains ranging from phone usage traces to data on the social Web. The analysis of user data is appealing to scientists who work on population studies, recommendations, and large-scale data analytics. We argue for the need for an interactive analysis to understand the multiple facets of user data and(More)
Mining frequent patterns is an essential task in discovering hidden correlations in datasets. Although frequent patterns unveil valuable information, there are some challenges which limits their usability. First, the number of possible patterns is often very large which hinders their effective exploration. Second, patterns with many items are hard to read(More)
In this study, we propose textual summarization for scientific publications and mobile phone usage patterns. Textual summarization is a process that takes a source document or set of related documents, identifying the most salient information and conveying it in less space than the original text. The increasing availability of information has necessitated(More)
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