COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM

<p align="justify">Agents of a complex system tend to naturally form groups or communities based on their similarities. In a network, these communities manifest themselves as bundles or densely connected nodes. Community detection is a prominent method for understanding the structure...

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Main Author: NURRIYADI SUPARNO (NIM : 10211053), ERVANO
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/21984
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:21984
spelling id-itb.:219842018-10-23T08:53:11ZCOMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM NURRIYADI SUPARNO (NIM : 10211053), ERVANO Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/21984 <p align="justify">Agents of a complex system tend to naturally form groups or communities based on their similarities. In a network, these communities manifest themselves as bundles or densely connected nodes. Community detection is a prominent method for understanding the structure, organization, and functioning of various real-world networks and has applications in diverse problems such as consensus formation in social communities and the identification of functional modules in biochemical networks. Current algorithms for identifying community structures in large-scale real-world networks generally require a priori information such as the number and sizes of communities and are computationally expensive. In this Final Project, we implement a simple label propagation algorithm that uses network structure alone as its guide and has an almost linear running time. In this algorithm, every node is initialized with a unique label, and at every step, each node adopts the label that most of its neighbors currently have. In this iterative process, densely connected groups of nodes form a consensus on a unique label to form communities. We then implement an agglomerative method to escape from local maxima and enhance the modularity. This combination of algorithm is known as advance label propagation algorithm. Finally, we validate the algorithm by applying it to networks whose community structures are known.<p align="justify"> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <p align="justify">Agents of a complex system tend to naturally form groups or communities based on their similarities. In a network, these communities manifest themselves as bundles or densely connected nodes. Community detection is a prominent method for understanding the structure, organization, and functioning of various real-world networks and has applications in diverse problems such as consensus formation in social communities and the identification of functional modules in biochemical networks. Current algorithms for identifying community structures in large-scale real-world networks generally require a priori information such as the number and sizes of communities and are computationally expensive. In this Final Project, we implement a simple label propagation algorithm that uses network structure alone as its guide and has an almost linear running time. In this algorithm, every node is initialized with a unique label, and at every step, each node adopts the label that most of its neighbors currently have. In this iterative process, densely connected groups of nodes form a consensus on a unique label to form communities. We then implement an agglomerative method to escape from local maxima and enhance the modularity. This combination of algorithm is known as advance label propagation algorithm. Finally, we validate the algorithm by applying it to networks whose community structures are known.<p align="justify">
format Final Project
author NURRIYADI SUPARNO (NIM : 10211053), ERVANO
spellingShingle NURRIYADI SUPARNO (NIM : 10211053), ERVANO
COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
author_facet NURRIYADI SUPARNO (NIM : 10211053), ERVANO
author_sort NURRIYADI SUPARNO (NIM : 10211053), ERVANO
title COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
title_short COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
title_full COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
title_fullStr COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
title_full_unstemmed COMMUNITY STRUCTURE DETECTION OF NETWORKS USING ADVANCED LABEL PROPAGATION ALGORITHM
title_sort community structure detection of networks using advanced label propagation algorithm
url https://digilib.itb.ac.id/gdl/view/21984
_version_ 1821120629892448256