Authors:
Paul Parau
;
Camelia Lemnaru
and
Rodica Potolea
Affiliation:
Technical University of Cluj-Napoca, Romania
Keyword(s):
Vertex Relevance, Commitment, Importance, Relative Commitment, Community Disruption.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Soft Computing
;
Symbolic Systems
;
Web Mining
Abstract:
The community structure of a network conveys information about the network as a whole, but it can also
provide insightful information about the individual vertices. Identifying the most relevant vertices in a network
can prove to be useful, especially in large networks. In this paper, we explore different alternatives for
assessing the relevance of a vertex based on the community structure of the network. We distinguish between
two relevant vertex properties - commitment and importance - and propose a new measure for quantifying
commitment, Relative Commitment. We also propose a strategy for estimating the importance of a vertex,
based on observing the disruption caused by removing it from the network. Ultimately, we propose a vertex
classification strategy based on commitment and importance, and discuss the aspects covered by each of the
two properties in capturing the relevance of a vertex.