Abstract
Nowadays, special kind of information gaining popularity is the one coming from social networks. In the paper we study basic statistical and graph-theoretical properties of the collaboration graph, which is an example of a large social network. To build such graph we use the data collected in the Rough Set Database System [9]. The collaboration graph contains data, among others, on Z. Pawlak, his co-authors, their co-authors, et cetera. In principle, the main idea presented in the paper is similar to the one of Erdos number [3], enriched with some concepts and techniques from social network analysis [1]. Analyzing our data we discover hidden patterns of collaboration among members of the rough set community [6],[8] which can be interesting for this community and others. Our data also provides fairly large, appealing real-life graphs on which one can test graph algorithms, in the spirit of [4].
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Suraj, Z., Grochowalski, P., Lew, Ł. (2011). Pawlak Collaboration Graph and Its Properties. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2011. Lecture Notes in Computer Science(), vol 6743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21881-1_56
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DOI: https://doi.org/10.1007/978-3-642-21881-1_56
Publisher Name: Springer, Berlin, Heidelberg
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