Paper: Random Graph Model Simulations of Semantic Networks for Associative Concept Dictionaries

ACL ID W08-2009
Title Random Graph Model Simulations of Semantic Networks for Associative Concept Dictionaries
Venue Coling 2008: Proceedings of the workshop on Speech Processing for Safety Critical Translation and Pervasive Applications
Session
Year 2008
Authors

Word asociation data in dictionary form can be simulated through the combina- tion 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 con- necting the two graphs. Such a model makes it posible to simulate the complex features in degree distributions and the interesting graph clustering results that are typically observed for real data. 1 Modeling background Asociative Concept Dictionaries (ACDs) consist of word pair data based on psychological ex- periments where the participants are typically asked to provide the semantically-related re- sponse word that comes to mind on presentation of a stimulus word. Two well-known ACDs for English are the University of South Florida word as...