Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7755

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Department: search.filters.department.İzmir Institute of Technology. Computer EngineeringScopus Q: search.filters.scopusQuartile.Q4

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  • Conference Object
    Citation - Scopus: 2
    A Comparative Study of Modularity-Based Community Detection Methods for Online Social Networks
    (CEUR Workshop Proceedings, 2018) Karataş, Arzum; Şahin, Serap
    Digital data represent our daily activities and tendencies. One of its main source is Online Social Networks (OSN) such as Facebook, YouTube etc. OSN are generating continuously high volume of data and define a dynamic virtual environment. This environment is mostly represented by graphs. Analysis of OSN data (i.e.,extracting any kind of relations and tendencies) defines valuable information for economic, socio-cultural and politic decisions. Community detection is important to analyze and understand underlying structure and tendencies of OSNs. When this information can be analysed successfully, software engineering tools and decision support systems can produce more successful results for end users. In this study, we present a survey of selected outstanding modularity-based static community detection algorithms and do comparative analysis among them in terms of modularity, running time and accuracy. We use different real-world OSN test beds selected from SNAP dataset collection such as Facebook Ego network, Facebook Pages network (Facebook gemsec), LiveJournal, Orkut and YouTube networks.
  • Conference Object
    Citation - Scopus: 2
    A Maximum Degree Self-Stabilizing Spanning Tree Algorithm
    (Springer Verlag, 2010) Çokuslu, Deniz; Erciyeş, Kayhan; Hameurlain, Abdelkader
    Spanning trees are fundamental topological structures in distributed environments which ease many applications that require frequent communication between nodes. In this paper, we examine and compare two spanning tree construction algorithms which rely on classical and self stabilization approach. Then, we propose a new self-stabilizing spanning tree construction algorithm which uses maximum degree heuristic while choosing the root node. We show experimentally that our new algorithm provides smaller tree diameters than the two existing approaches with favorable run-times. © 2011 Springer Science+Business Media B.V.