A parameterized greedy algorithm for cluster editing

Computer technology has allowed the business and research communities to amass huge amounts of data in electronic form. The data per se is of little use. What owners of the data require is analysis of its content, resulting in information that can then be used, for example, to influence future decisions or solve problems. This paper presents a new algorithm for automated processing of data sets to produce information from the data, or to indicate that no such information exists. The techniques are proven to be mathematically correct, and examples are used to demonstrate application of the technique.