Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present an algorithm for decomposing a social network into an optimal number of structurally equivalent classes. The k-means method is used to determine the best decomposition of the social network for various numbers of subgroups. The best number of subgroups into which to decompose a network is determined by minimizing the intra-cluster variance of similarity subject to the constraint that the improvement in going to more subgroups is better than a random network would achieve.  also describe a decomposability metric that assesses how closely the derived decomposition approaches an ideal network having only structurally equivalent classes.#R##N##R##N#Three ll-known network data sets re used to demonstrate the algorithm and decomposability metric. These demonstrations indicate the utility of the approach and suggest how it can be used in a complementary way to Generalized Blockmodeling.
['Mo-Han Hsieh', 'Christopher L. Magee']
I am writing a research paper on a idea An algorithm and metric for network decomposition from similarity matrices: Application to positional analysis
[{"from": "human", "value": "I am writing a research paper on a idea An algorithm and metric for network decomposition from similarity matrices: Application to positional analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present an algorithm for decomposing a social network into an optimal number of structurally equivalent classes. The k-means method is used to determine the best decomposition of the social network for various numbers of subgroups. The best number of subgroups into which to decompose a network is determined by minimizing the intra-cluster variance of similarity subject to the constraint that the improvement in going to more subgroups is better than a random network would achieve.  also describe a decomposability metric that assesses how closely the derived decomposition approaches an ideal network having only structurally equivalent classes.#R##N##R##N#Three ll-known network data sets re used to demonstrate the algorithm and decomposability metric. These demonstrations indicate the utility of the approach and suggest how it can be used in a complementary way to Generalized Blockmodeling."}]