Community Detection in Networks using Node Attributes and Modularity
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2017, Vol 8, Issue 1
Abstract
Community detection in network is of vital importance to find cohesive subgroups. Node attributes can improve the accuracy of community detection when combined with link information in a graph. Community detection using node attributes has not been investigated in detail. To explore the aforementioned idea, we have adopted an approach by modifying the Louvain algorithm. We have proposed Louvain-AND-Attribute (LAA) and Louvain-OR-Attribute (LOA) methods to analyze the effect of using node attributes with modularity. We compared this approach with existing community detection approaches using different datasets. We found the performance of both algorithms better than Newman’s Eigenvector method in achieving modularity and relatively good results of gain in modularity in LAA than LOA. We used density, internal and external edge density for the evaluation of quality of detected communities. LOA provided highly dense partitions in the network as compared to Louvain and Eigenvector algorithms and close values to Clauset. Moreover, LOA achieved few numbers of edges between communities.
Authors and Affiliations
Yousra Asim, Rubina Ghazal, Wajeeha Naeem, Abdul Majeed, Basit Raza, Ahmad Kamran Malik
Keywords
Related Articles
- EP ID EP250540
- DOI 10.14569/IJACSA.2017.080148
- Views 93
- Downloads 0
A DISTRIBUTED KEY BASED SECURITY FRAMEWORK FOR PRIVATE CLOUDS
Cloud computing in its various forms continues to grow in popularity as organizations of all sizes seek to capitalize on the cloud’s scalability, externalization of infrastructure and administration and generally reduced...
An Intelligent Bio-Inspired Algorithm for the Faculty Scheduling Problem
All universities have faculty members who need to be assigned to teach courses. Those members have various specialties, preferences and different levels of experience. The manual assignment of courses is a very tedious a...
Improved Sliding Mode Nonlinear Extended State Observer based Active Disturbance Rejection Control for Uncertain Systems with Unknown Total Disturbance
This paper presents a new strategy for the active disturbance rejection control (ADRC) of a general uncertain system with unknown bounded disturbance based on a nonlinear sliding mode extended state observer (SMESO). Fir...
The Computation of Assimilation of Arabic Language Phonemes
The computational phonology is fairly a new science that deals with studying phonological rules under the computation point of view. Computational phonology is based on the phonological rules, which are the processes tha...
Distributed GPU-Based K-Means Algorithm for Data-Intensive Applications: Large-Sized Image Segmentation Case
K-means is a compute-intensive iterative algorithm. Its use in a complex scenario is cumbersome, specifically in data-intensive applications. In order to accelerate the K-means running time for data-intensive application...