Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of Pearson’s correlation coefficient in Author Cocitation Analysis was compared with Salton’s cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. Hover, one has the option of applying a logarithmic transformation in correlation analysis. Information calculus is based on both the logarithmic transformation and provides a non-parametric statistics. Using this methodology one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used on the data set which was made the subject of this discussion.
['Loet Leydesdorff']
I am writing a research paper on a idea Similarity Measures, Author Cocitation Analysis, and Information Theory
[{"from": "human", "value": "I am writing a research paper on a idea Similarity Measures, Author Cocitation Analysis, and Information Theory"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The use of Pearson\u2019s correlation coefficient in Author Cocitation Analysis was compared with Salton\u2019s cosine measure in a number of recent contributions. Unlike the Pearson correlation, the cosine is insensitive to the number of zeros. Hover, one has the option of applying a logarithmic transformation in correlation analysis. Information calculus is based on both the logarithmic transformation and provides a non-parametric statistics. Using this methodology one can cluster a document set in a precise way and express the differences in terms of bits of information. The algorithm is explained and used on the data set which was made the subject of this discussion."}]