The volume of data being generated nowadays is increasingly large. How to extract useful information from such data collections is an important issue. A promising technique is the Rough set theory, a new mathematical approach to data analysis based on classification of objects of interest into similarity classes which are indiscernible with respect to some features. This theory offers two funda...

This paper describes a rule discovery system that has been developed as part of an ongoing research project. The system allows discovery of multirelational rules using data from relational databases. The basic assumption of the system is that objects to be analyzed are stored in a set of tables. Multirelational rules discovered would either be used in predicting an unknown object attribute valu...

Graded classification occurs in many areas of IT, e.g. user preference, relevance, rating, investment, business competitiveness but also in IR, semantic web, multimedia databases. In this paper we define the graded classification ILP task. Namely having a classified learning data, we want to learn the classification function depending on other attributes. We introduce a procedure based on multi...

GRD is an algorithm for k-most interesting rule discovery. In contrast to association rule discovery, GRD does not require the use of a minimum support constraint. Rather, the user must specify a measure of interestingness and the number of rules sought (k). This paper reports efficient techniques to extend GRD to support mining of negative rules.

This paper gives a survey of contrast set mining (CSM), emerging pattern mining (EPM), and subgroup discovery (SD) in a unifying framework named supervised descriptive rule discovery. While all these research areas aim at discovering patterns in the form of rules induced from labeled data, they use different terminology and task definitions, claim to have different goals, claim to use different...

This paper describes the application of data mining techniques in a Geo-spatial Decision Support System, which focuses on drought risk management. Association rule discovery is one of the widely used approaches in data mining. This paper highlights the rule discovery algorithms that we have developed and used for discovering useful patterns in ocean parameters and climatic indices to monitor dr...

This paper describes the application of data mining techniques in a National Drought Decision Support System, which focuses on drought risk management. Association rule discovery is one of the widely used approaches in data mining. This paper highlights the rule discovery algorithms that we have developed and used for discovering useful patterns in ocean parameters and climatic indices.