The Transactions in web data often consist of quantitative data, suggesting that fuzzy set theory can be used to represent such data. The time spent by users on each web page is one type of web data, was regarded as a trapezoidal membership function (TMF) and can be used to evaluate user browsing behavior. The quality of mining fuzzy association rules depends on membership functions and since t...

We present new methods for pruning and enhancing itemsets for text classification via association rule mining. Pruning methods are based on dependency syntax and enhancing methods are based on replacing words by their hyperonyms of various orders. We discuss the impact of these methods, compared to pruning based on tfidf rank of words.

The discovery of association rules has been known to be useful in selective marketing, decision analysis, and business management. An important application area of mining association rules is the market basket analysis, which studies the buying behaviors of customers by searching for sets of items that are frequently purchased together. With the increasing use of the record-based databases whos...

Association rule mining is a well established and popular data mining method for finding local dependencies between items in large transaction databases. However, a practical drawback of mining and efficiently using association rules is that the set of rules returned by the mining algorithm is typically too large to be directly used. Clustering association rules into a small number of meaningfu...

Frequent item sets mining plays an important role in association rules mining. A variety of algorithms for finding frequent item sets in very large transaction databases have been developed. Although many techniques were proposed for maintenance of the discovered rules when new transactions are added, little work is done for maintaining the discovered rules when some transactions are deleted fr...

We have a large database consisting of user proole information together with behavioral patterns. We introduce the concept of proole association rules, which discusses the problem of relating consumer buying behavior to behavioral information. We investigate the problem of online mining of proole association rules in this large database. We show how to use multidimensional indexing structures i...

In recent years, extensive research has been carried out by focusing on association rules to build more accurate classifiers. These integrated approaches mainly focus on a limited subset of association rules, i.e. those rules where the consequent of the rule is restricted to the classification class attribute. This paper aims to contribute to this integrated framework by adapting the CBA (Class...

Several notions of redundancy exist for Association Rules. Often, these notions take the form “any dataset in which this first rule holds must obey also that second rule, therefore the second is redundant”; if we see datasets as interpretations (or models) in the logical sense, this is a form of logical entailment. In many logics, entailment has a syntactic counterpart in the form of a deductio...