Enhanced Data Using Positive Negative Association Mining

Computer Engineering

Knowledge discovery is the process of analysing data from different perspectives and summarizing it into useful information. Association rule mining is a data mining process used widely in traditional databases to find the positive association rules. Association rules are created by analysing data for frequent patterns and by using the criteria support and confidence to identify the most important relationships. However, there are some other challenging rule mining topics like negative association rule mining. In this research, a rule mining approach has been proposed that provides efficient and secure solution using positive and negative association rule computation on Asynchronous JavaScript and XML (AJAX) data. By using AJAX, we get the faster and secure retrieval of data. Whenever you given the input dataset it will retrieve percentage value of positive negative association rule and attributes of datasets that positively or negatively associated

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