E-commerce is snowballing with advancements in technology, and as a result,
understanding complex transactional data has become increasingly important. To keep …

Variable refrigerant flow systems account for a considerable portion of energy consumption
in buildings. In order to improve the energy efficiency and estimate the energy saving …

A novel framework for mining temporal association rules by discovering itemsets with
frequent itemsets tree is introduced. In order to solve the problem of handling time series by …

Temporal pattern mining is the recent research among researchers contributing in the areas
of data mining, medical mining, spatial data mining, health informatics and gaining …

The improvements in tuning the website and improving the visitors' retention are done by
deploying the efficient weblog mining and navigational pattern prediction model. This crucial …

Temporal data contain time-stam** information that affects the results of data mining.
Traditional techniques for finding frequent itemsets assume that datasets are static and the …

Temporal database is a database which captures and maintains past, present and future
data. Conventional databases are not suitable for handling such time varying data. In this …

The problem of mining frequent patterns in non-temporal databases is studied extensively.
Conventional frequent pattern algorithms are not applicable to find temporal frequent items …

Most recommender systems usually combine several recommendation methods to enhance
the recommendation accuracy. Collaborative filtering (CF) is a best-known personalized …

In real-world applications, transactions are typically represented by quantitative data. Thus,
fuzzy association rule mining algorithms have been proposed to handle these quantitative …