Frequent itemset mining allows us to find hidden, important information from large
databases. Moreover, processing incremental databases in the itemset mining area has …

The advent of web‐based applications and services has created such diverse and
voluminous web log data stored in web servers, proxy servers, client machines, or …

Traditional temporal association rules mining algorithms cannot dynamically update the
temporal association rules within the valid time interval with increasing data. In this paper, a …

In the real world database updates continuously in several online applications like super
market, network monitoring, web administration, stock market etc. Frequent pattern mining is …

This paper proposes a new recommending method using effective purchase pattern mining
with weight based on FRAT (Frequency, Regency, Amount and Type of merchandise or …

One of the most challenging areas in data mining is Association rule mining. Several
algorithms have been developed to solve this problem. These algorithms work efficiently …

Nowadays, due to escalating the demands of the direct purchase of e-commerce with many
kinds of item, the demand for e-commerce is exploding. The recommender system finds …

Mining temporal association rules is a very interesting topic, which is applied in many
applications nowadays. In temporal databases, each item has its own lifetime period, called …

Association rule mining is a popular data mining technique which gives us valuable
relationships among different items in a dataset. In dynamic databases, new transactions are …

The discovery of association relationship among a huge database has been known to be
useful in selective marketing, decision analysis, and business management. The current …