Please use this identifier to cite or link to this item:
Title: Multiresolution organization of social media users' profiles: fast detection and efficient transmission of characteristic profiles
Authors: Ntalianis, Klimis S. 
Tsapatsoulis, Nicolas 
Keywords: Social media;Multiresolution organization;Social computing;Profiles' visualization
Category: Computer and Information Sciences
Field: Natural Sciences
Issue Date: 30-Jan-2018
Publisher: IEEE
Source: Joint 10th IEEE International Conference on Internet of Things, iThings 2017, 13th IEEE International Conference on Green Computing and Communications, GreenCom 2017, 10th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2017 and the 3rd IEEE International Conference on Smart Data, Smart Data 2017, 2017, Exeter, United Kingdom, 21-23 June
Abstract: In this paper, multiresolution organization of social media users' profiles is proposed that enables fast browsing and effective transmission of characteristic profiles. The scheme results in the construction of a novel three-layer tree structure. At layer 0 the root-node contains the most representative profile among class representatives (CRs). Each node of layer 1 represents a class of profiles, while in layer 2 the full resolution is available (all profiles). The nodes of the proposed tree structure contain viewing elements and in this paper we focus on the extraction of viewing elements for layers 0, and 1. Towards this direction the viewing elements of layer 1 are optimally extracted using an interpolation method, while the viewing element of layer 0 is estimated from the viewing elements of layer 1. The resulting tree-structure enables users to quickly browse and detect profiles of interest, by selecting the viewing elements they like. Experimental results on reallife social media users indicate the promising performance of this innovative scheme.
Rights: © 2017 IEEE.
Type: Conference Papers
Appears in Collections:Δημοσιεύσεις σε συνέδρια/Conference papers

Show full item record

Page view(s)

Last Week
Last month
checked on Aug 21, 2019

Google ScholarTM


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.