Abstract
For the structure analysis of non-metric data, it is natural to classify objects according to the properties they possess. An effective model to analyze the structure of similarities between objects is the random intersection graph generated by the random bipartite graph with bipartition \((\mathcal{V},\mathcal{W})\), where \(\mathcal{V}\) is a set of objects, \(\mathcal{W}\) is a set of properties, and according to some random procedure, edges join objects with their properties. In the related random intersection graph two vertices are joined by an edge if and only if they represent objects sharing at least s properties. In this paper we study the number of isolated vertices and its convergence to Poisson distribution. We generalize previous results obtained for special cases of the random model and for s = 1, only. Our approach leads us also to some interesting results on dependencies between the appearances of edges in the random intersection graph.
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References
Bloznelis, M., Jaworski, J., & Rybarczyk, K. (2009). Component evolution in a secure wireless sensor network. Networks, 53, 19–26.
Bock, H. H. (1996). Probabilistic models in cluster analysis. Computational Statistics and Data Analysis, 23, 5–28.
Godehardt, E. (1990). Graphs as structural models. Braunschweig: Vieweg.
Godehardt, E., & Jaworski, J. (2002). Two models of random intersection graphs for classification. In M. Schwaiger, & O. Opitz (Eds.), Exploratory data analysis in empirical research (pp. 68–81). Berlin Heidelberg New York: Springer.
Godehardt, E., Jaworski, J., & Rybarczyk, K. (2007). Random intersection graphs and classification. In R. Decker, & Lenz, H.-J. (Eds.), Advances in data analysis (pp. 67–74). Berlin Heidelberg New York: Springer.
Karoński, M., Scheinerman, E. R., & Singer-Cohen, K. B. (1999). On random intersection graphs: The subgraph problem. Combinatorics, Probability and Computing, 8, 131–159.
Acknowledgements
J. Jaworski and K. Rybarczyk acknowledges the support by Ministry of Science and Higher Education, grant N N206 2701 33, 2007–2010. This work also had been supported by the Deutsche Forschungsgesellschaft (grant no. GO 490/13-1, GO 490/15-1).
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Godehardt, E., Jaworski, J., Rybarczyk, K. (2009). Isolated Vertices in Random Intersection Graphs. In: Fink, A., Lausen, B., Seidel, W., Ultsch, A. (eds) Advances in Data Analysis, Data Handling and Business Intelligence. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01044-6_12
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DOI: https://doi.org/10.1007/978-3-642-01044-6_12
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