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Communication Dans Un Congrès Année : 2015

Interactive User Group Analysis

Résumé

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 address different analytics scenarios. Since user data is often sparse and noisy, we propose to produce labeled groups that describe users with common properties and develop IUGA, an interactive framework based on group discovery primitives to explore the user space. At each step of IUGA, ananalyst visualizes group members and may take an action on the group (add/remove members) and choose an operation (exploit/explore) to discover more groups and hence more users. Each discovery operation results in k most relevant and diverse groups. We formulate group exploitation and exploration as optimization problems and devise greedy algorithms to enable efficient group discovery. Finally, we design a principled validation methodology and run extensive experiments that validate the effectiveness of IUGA on large datasets for different user space analysis scenarios.
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Dates et versions

hal-01178784 , version 1 (20-07-2015)

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  • HAL Id : hal-01178784 , version 1

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Behrooz Omidvar Tehrani, Sihem Amer-Yahia, Alexandre Termier. Interactive User Group Analysis. 24th ACM International Conference on Information and Knowledge Management (CIKM 2015), ACM, Oct 2015, Melbourne, Australia. ⟨hal-01178784⟩
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