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Time-aware Egocentric network-based User Profiling

Abstract : Improving the egocentric network-based user's profile building process by taking into account the dynamic characteristics of social networks can be relevant in many applications. To achieve this aim, we propose to apply a time-aware method into an existing egocentric-based user profiling process, based on previous contributions of our team. The aim of this strategy is to weight user's interests according to their relevance and freshness. The time awareness weight of an interest is computed by combining the relevance of individuals in the user's egocentric network (computed by taking into account the freshness of their ties) with the information relevance (computed by taking into account its freshness). The experiments on scientific publications networks (DBLP/Mendeley) allow us to demonstrate the effectiveness of our proposition compared to the existing time-agnostic egocentric network-based user profiling process.
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Submitted on : Thursday, July 7, 2016 - 1:19:22 PM
Last modification on : Tuesday, September 8, 2020 - 10:36:09 AM


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  • HAL Id : hal-01343052, version 1
  • OATAO : 15356


Marie-Françoise Canut, Sirinya On-At, André Péninou, Florence Sèdes. Time-aware Egocentric network-based User Profiling. 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2015), Aug 2015, Paris, France. pp. 569-572. ⟨hal-01343052⟩



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