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StrCoBSP: Relationship Strength-Aware Community-Based Social Profiling

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Information Management and Big Data (SIMBig 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1410))

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Abstract

User interest inference in social media is an important research topic with great value in modern personalization and advertisement systems. Using relationships characteristics such as strength may allow more refined inference. Indeed, due to influence and homophily phenomena, people maintaining strongest relationships tend to be and become more similar. Accordingly, we present StrCoBSP a Strength-aware Community-Based Social Profiling process that combines community structure and relationship strength to predict user’s interests in his egocentric network. We present empirical evaluation of StrCoBSP performed on real world co-authorship networks (DBLP/ResearchGate). The performances of the proposed approach are superior to the ones achieved by the existing strength-agnostic process with lifts of up to 18,46% and 18,15% in terms of precision and recall at top 15 returned interests.

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Authors and Affiliations

  1. Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar Algiers, Algeria

    Asma Chader, Hamid Haddadou, Leila Hamdad & Walid-Khaled Hidouci

Authors
  1. Asma Chader
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  2. Hamid Haddadou
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  3. Leila Hamdad
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  4. Walid-Khaled Hidouci
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Corresponding author

Correspondence to Asma Chader .

Editor information

Editors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Juan Antonio Lossio-Ventura

  2. Visibilia, São Paulo, Brazil

    Jorge Carlos Valverde-Rebaza

  3. University of Valencia, Valencia, Spain

    Eduardo Díaz

  4. Universidad del Pacífico, Lima, Peru

    Hugo Alatrista-Salas

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Chader, A., Haddadou, H., Hamdad, L., Hidouci, WK. (2021). StrCoBSP: Relationship Strength-Aware Community-Based Social Profiling. In: Lossio-Ventura, J.A., Valverde-Rebaza, J.C., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2020. Communications in Computer and Information Science, vol 1410. Springer, Cham. https://doi.org/10.1007/978-3-030-76228-5_24

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  • DOI: https://doi.org/10.1007/978-3-030-76228-5_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76227-8

  • Online ISBN: 978-3-030-76228-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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