Interactive User Group Analysis

Behrooz Omidvar Tehrani 1 Sihem Amer-Yahia 1 Alexandre Termier 2
2 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : 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.
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-01178784
Contributor : Alexandre Termier <>
Submitted on : Monday, July 20, 2015 - 8:19:30 PM
Last modification on : Saturday, December 15, 2018 - 1:49:53 AM

Identifiers

  • HAL Id : hal-01178784, version 1

Citation

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⟩

Share

Metrics

Record views

469