finding frequent patterns plays a key role in exploring association patterns, correlation, and many other interesting relationships that are applicable in tdb. several association rule mining algorithms such as apriori, fp-growth, and eclat have been proposed in the literature. fp-growth algorithm construct a tree structure from transaction database and recursively traverse this tree to extract...

In [?] Lin, Wang and Zhou propose the iterative Toeplitz filters algorithm as an alternative iterative algorithm for EMD. In this alternative algorithm, the average of the upper and lower envelopes is replaced by certain “moving average” obtained through a low-pass filter. Performing the tradition sifting algorithm with such moving averages is equivlalent to iterating certain convolution filter...

The web has become the world's largest repository of knowledge. Web usage mining is the process of discovering knowledge from the interactions generated by the user in the form of access logs, cookies, and user sessions data. Web Mining consists of three different categories, namely Web Content Mining, Web Structure Mining, and Web Usage Mining (is the process of discovering knowledge from the ...

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...

Nowadays companies measure suppliers on the basis of a variety of factors and criteria that affect the supplier's selection issue. This paper intended to identify the key effective criteria for selection of green suppliers through an efficient algorithm callediterative process mining or i-PM. Green data were collected first by reviewing the previous studies to identify various environmental cri...

Process mining and visual analytics are two disciplines that emerged over the last decade. The goal of process mining is to use event data to extract process-related information, e.g., to automatically discover a process model by observing events recorded by some information system or to check the conformance of a process model with actual process executions. The spectacular growth of event dat...