Multi-application Personalization: Data Propagation Evaluation on a Real-life Search Query Log

Marco Viviani Nadia Bennani 1 Elod Egyed-Zsigmond 1 Lyes Limam 1 David Coquil
1 DRIM - Distribution, Recherche d'Information et Mobilité
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In the field of multi-application personalization, several techniques have been proposed to support user modeling. None of them have sufficiently investigated the opportunity for a multi-application profile to evolve over time in order to avoid data inconsistency and the subsequent loss of income for website users and companies. In this paper, we propose a model addressing this issue and we focus in particular on user profile data propagation management, as a way to reduce the amount of inconsistent user profile information over several applications. To evaluate our model, we first extract user profiles using logs of the large real-life AOL search engine. Then, we simulate data propagation along semantically related user information.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01352989
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Submitted on : Wednesday, August 10, 2016 - 4:18:04 PM
Last modification on : Monday, December 10, 2018 - 5:51:46 PM

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Marco Viviani, Nadia Bennani, Elod Egyed-Zsigmond, Lyes Limam, David Coquil. Multi-application Personalization: Data Propagation Evaluation on a Real-life Search Query Log. 6th IEEE International Conference on Digital Ecosystems Technologies-Complex Environment Engineering, Jun 2012, Campione, Italy. pp.1-6, ⟨10.1109/DEST.2012.6227917⟩. ⟨hal-01352989⟩

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