Investigating the fine grained structure of networks
Name
679673969-MIT.pdf
Description
Full printable version
Size
6.36 MB
Format
Adobe PDF
Checksum (MD5)
91256c677bbd4cee372c7422cc972429
Author(s)
Macindoe, Owen
Advisor(s)
Whitman Richards.
Date Issued
2010
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis I explore a novel representation for characterizing a graph's fine grained structure. The key idea is that this structure can be represented as a distribution of the structural features of subgraphs. I introduce a set of such structural features and use them to compute representations for a variety of graphs, demonstrating their use in qualitatively describing fine structure. I then demonstrate the utility of this representation with quantitative techniques for computing graph similarity and graph clustering. I show that similarity judged using this representation is significantly different from judgements using full graph structural measures. I find that graphs from the same class of networks, such as email correspondence graphs, can differ significantly in their fine structure across the institutions whose relations they model, but also find examples of graphs from the same institutions across different time periods that share a similar fine structure.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student submitted PDF version of thesis.
Includes bibliographical references (p. 107-109).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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