Mining frequent itemsets and association rules are an essential task within data mining analysis. In this paper, we introduce PrefRec, a recursive algorithm for finding rules. Its main advantage is its recursiveness with respect to the items. It particularly efficient updating process when new items added database or some excluded. We present in complete way logic of algorithm, give application...

An integrated approach of mining association rules and meta-rules based on a hyper-structure is put forward. In this approach, time serial databases are partitioned according to time segments, and the total number of scanning database is only twice. In the first time, a set of 1-frequent itemsets and its projection database are formed at every partition. Then every projected database is scanned...

Competitive intelligence (CI) has become one of the major subjects for researchers in recent years. The present research is aimed to achieve a part of the CI by investigating the scientific articles on this field through text mining in three interrelated steps. In the first step, a total of 1143 articles released between 1987 and 2016 were selected by searching the phrase "competitive intellige...

The problem of mining association rules in a database are introduced. Most of association rule mining approaches aim to mine association rules considering exact matches between items in transactions. A new algorithm called ―Without expert fuzzy based data mining Based on Fuzzy Similarity to mine new Association Rules ‖ which considers not only exact matches between items, but also the fuzzy sim...