Random graph model simulations of semantic networks for associative concept dictionaries

Authors:
Hiroyuki Akama;Jaeyoung Jung;Terry Joyce;Maki Miyake
Affiliations:
Tokyo Institute of Technology, Tokyo, Japan;Tokyo Institute of Technology, Tokyo, Japan;Tama University, Kanagawa-ken, Japan;Osaka University, Osaka, Japan
Venue:
TextGraphs-3 Proceedings of the 3rd Textgraphs Workshop on Graph-Based Algorithms for Natural Language Processing
Year:
2008

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Capturing the structures in association knowledge: application of network analyses to large-scale databases of Japanese word associations

LKR'08 Proceedings of the 3rd international conference on Large-scale knowledge resources: construction and application

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Abstract

Word association data in dictionary form can be simulated through the combination of three components: a bipartite graph with an imbalance in set sizes; a scale-free graph of the Barabási-Albert model; and a normal distribution connecting the two graphs. Such a model makes it possible to simulate the complex features in degree distributions and the interesting graph clustering results that are typically observed for real data.