-Data Mining can be delineated as an action that analyze the data and draws out some new nontrivial information from the large amount of databases. Traditional data mining methods have focused on finding the statistical correlations between the items that are frequently appearing in the database. High utility itemset mining is an area of research where utility based mining is a descriptive type...

In this paper we define the notion of cause-effect sequential patterns from action traces. These patterns reflect causality relations according to background knowledge. We also present an algorithm for mining cause-effect patterns from a collection of action traces. We run this algorithm on a real-world domain and observe that causeeffect patterns can be computed efficiently by quickly identify...

This paper presents an approach of case mining to automatically discover case bases from large datasets in order to improve both the speed and the quality of case based reasoning. Case mining constructs a case base from a large raw dataset with an objective to improve the case-base reasoning systems’ efficiency and quality. Our approach starts from a raw database of objects with class attribute...

industrial-scale r&d it projects depend on many sub-technologies which need to be understood and have their risks analysed before the project can begin for their success. when planning such an industrial-scale project, the list of technologies and the associations of these technologies with each other is often complex and form a network. discovery of this network of technologies is time con...

theoretical review of ‘mining pit lakes’ indicates that like natural lakes such lakes display a huge diversity. they are typically in a non-equilibrium state with respect to their surroundings. hence, at the decommissioning phase of mining operation a detailed technical study are required on different aspects of such created water bodies considering its morphometry, geology, hydrology, water qu...