COMBINED: COmmunity Mining By Inducing Node & Edge Data

Desai, Mittul (2016) COMBINED: COmmunity Mining By Inducing Node & Edge Data. Masters thesis, Indian Institute of Technology Hyderabad.

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Community Detection is the process of identifying a group of nodes in a graph that are distinguish- able in some context. Two sources of information have been studied in detail by the community namely: Edge Structure and Node Attributes. Most work only deals with one of the above meth- ods. However there is some work in the recent years that use them to complement each other. In this paper, we aim to add a new dimension to the problem namely, edge attributes . In addition to using the aforementioned methods we add edge attributes to detect communities. Edge attributes uncover micro-communities that might not be easily retrievable using Node attributes and Edge Structure. Especially in social networks, edge attributes might constitute a large part of the in- formation content. This information along with contextual information of the edge helps uncover previously undisclosed communities. It also helps uncover disjoint and overlapping communities. Our approach uncovers the related attributes that form the community.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Thesis (Masters)
Uncontrolled Keywords: Community Detection, Social Mining, TD651
Subjects: Computer science > Big Data Analytics
Divisions: Department of Computer Science & Engineering
Depositing User: Team Library
Date Deposited: 09 Sep 2016 10:35
Last Modified: 30 Jul 2019 05:43
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