Mining association rules associates events that took place together. In market basket analysis, these discovered rules associate items purchased together. Items that are not part of a transaction are not considered. In other words, typical association rules do not take into account items that are part of the domain but that are not together part of a transaction. Association rules are based on ...

data sanitization is a process that is used to promote the sharing of transactional databases among organizations and businesses, it alleviates concerns for individuals and organizations regarding the disclosure of sensitive patterns. it transforms the source database into a released database so that counterparts cannot discover the sensitive patterns and so data confidentiality is preserved ag...

Data mining is a field encompassing study of the tools and techniques to assist humans in intelligently analyzing (mining) mountains of data. Data mining has found successful applications in many fields including sales and marketing, financial crime identification, portfolio management, medical diagnosis, manufacturing process management and health care improvement etc.. Data mining techniques ...

This paper addresses the problem of pattern management in the framework of formal concept analysis using restrictions on objects or attributes of a given data set. Patterns are pieces of information/knowledge with a concise description that can be obtained from data using data mining techniques. These can be clusters or bi-clusters, implications or association rules, and so on. Even for relativ...

This study analyzes the purchase patterns of MPEG Audio Layer-3 Players (MP3) customers in Korea. Factor analysis, clustering, and association rules are used to find the purchase patterns of segmented groups. From our analysis, 7 major factors were identified: technique, business, stylishness, rationale, late adaptor, pragmatic propensity, and music. Based on these factors and demographic data,...

Association mining is one of the most used data mining techniques due to interpretable and actionable results. In this study we propose a framework to visualize the association mining results, specifically frequent itemsets and association rules, as graphs. We demonstrate the applicability and usefulness of our approach through a Market Basket Analysis (MBA) case study where we visually explore...

Since the earlier work in [2], a broad variety of data mining capabilities has been developed. These studies cover a broad spectrum of topics including: (1) association rule mining [1, 3, 11, 17]; (2) incremental updating [7, 14]; (3) mining of generalized [20], multi-level [8], multi-dimensional rules [22, 23]; (4) constraint-based rule mining [9, 18]; (5) temporal association rule [6, 13, 21]...

We are presently exploring the idea of discovering association rules in medical data. There are several technical aspects which make this problem challenging. In our case medical data sets are small, but have high dimensionality. Information content is rich: there exist numerical, categorical, time and even image attributes. Data records are generally noisy. We explain how to map medical data t...

In the south area of China, there covers thick soil and flourish vegetation on the top of the rocks, so there is little research on lithology analysis by remote sensing in the south area, and there is also no mature methods on this aspect. Three Gorges are the south area which is thickly covered by soil and flourish vegetation and the lithology analysis is very difficult. Three Gorges possess t...