This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
Association rule mining in real-time is of increasing thrust in many business applications. Applications such as e-commerce, recommender systems, supply-chain management and group...
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usagebased approach to generate recommendations that ...