We present an algorithm for mining association rules from relational tables containing numeric and categorical attributes. The approach is to merge adjacent intervals of numeric v...
Discovery of association rules from large databases of item sets is an important data mining problem. Association rules are usually stored in relational databases for future use i...
Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the dat...
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
The problem of finding association rules in a large database of sales transactions has been widely studied in the literature, We discuss some of the weaknessesof the large itemset...
Mining association rules is an important data mining problem. Association rules are usually mined repeatedly in different parts of a database. Current algorithms for mining associa...
Association rules are a class of important regularities in databases. They are found to be very useful in practical applications. However, the number of association rules discovere...
—Association rules are useful for determining correlations between attributes of a relation and have applications in the marketing, financial, and retail sectors. Furthermore, op...
In this paper, we introduce a frame metadata model to facilitate the continuous association rules of web transactions. A new set of association rules can be derived with the updat...
A new extension of the Boolean association rules, ordinal association rules, that incorporates ordinal relationships among data items, is introduced. One use for ordinal rules is ...