Unformatted text preview: (b) Compare the algorithms using enron2.txt: i. plot performance vs. density threshold for diﬀerent algorithms ii. plot clustering coeﬃcient vs. number of nodes deleted (up to top 10%) for diﬀerent algorithms [Figure 5b in the paper] iii. discuss the relative performance of diﬀerent algorithms 6. Implementation: (a) use one of these programming languages: C, C++, Java, or LISP. (b) input ﬁle: a ﬁle for vertices and edges (c) two modules: i. BridgeCut: input graph; output: • top edge/vertex when it is removed • for each cluster, output vertices in the cluster ii. Evaluate: input vertices and cluster membership; output performance 7. Submission: (a) source code (b) your data set (c) report in pdf (d) README.txt (how to compile and run your program on code.ﬁt.edu)...
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- Fall '09
- Graph Theory, Sensitivity analysis, Computer program, density threshold