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On approximate nesting of multiple social network graphs: a preliminary study

Published: 10 June 2019 Publication History

Abstract

A fundamental problem in Social Network Analysis is how to move from single-layer to multi-layer, which provide a holistic view. User profiles resolution has received considerable attention since it allows to match users on different online social networks (OSNs). However, to the best of our knowledge, no study has focused on nesting operation for merging OSNs graphs. This work is a first step in the direction of defining the data model and the algorithm to perform approximate nesting of multiple OSNs graphs, based on user features. We provide initial experimental evidence based on synthetic data.

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cover image ACM Other conferences
IDEAS '19: Proceedings of the 23rd International Database Applications & Engineering Symposium
June 2019
364 pages
ISBN:9781450362498
DOI:10.1145/3331076
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 10 June 2019

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Author Tags

  1. approximate graph query answering
  2. graph nesting
  3. multilayer social networks

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IDEAS 2019

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Overall Acceptance Rate 74 of 210 submissions, 35%

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View all
  • (2024)Exploring the Internal Defense System of Cerastoderma glaucum (Bruguière, 1789) Exposed to Pristine Microplastics: The Sentinel Role of Haemocytes as BiomarkersFishes10.3390/fishes90602419:6(241)Online publication date: 20-Jun-2024
  • (2023)Edge Local Differential Privacy for Dynamic GraphsSecurity and Privacy in Social Networks and Big Data10.1007/978-981-99-5177-2_13(224-238)Online publication date: 3-Aug-2023
  • (2021)Explainable Data Analytics for Disease and Healthcare Informatics25th International Database Engineering & Applications Symposium10.1145/3472163.3472175(65-74)Online publication date: 14-Jul-2021

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