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This paper presents a layered approach to analysis and visualization of associations from events. The proposed approach provides different levels of abstraction for aggregating and analyzing events from heterogeneous data sources by using lists and customizable functions. Interfaces for creating lists and functions are also implemented for different levels of users. The effectiveness of the proposed...
Data mining is comprised of many data analysis techniques. Its basic objective is to discover the hidden and useful data pattern from very large set of data. Graph mining, which has gained much attention in the last few decades, is one of the novel approaches for mining the dataset represented by graph structure. Graph mining finds its applications in various problem domains, including: bioinformatics,...
Data Mining is concerned with extraction of interesting patterns or knowledge from huge amounts of Data. Generally data mining tasks are either predictive or descriptive. Classification falls under predictive induction while clustering and association rule mining fall under descriptive induction. Subgroup discovery is a task at the intersection of supervised learning and descriptive induction. In...
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