In the research field of automated process discovery and analysis, purity event log datasets ought to be a matter vital importance success discovering sound exact models. Moreover, there exist various types anomalies that result in inaccurate models from enactment datasets. A peculiar one out these anomalies, which is core challenging issue this paper, temporal activity-sequencing anomaly criti...

Data mining is the process that attempts to discover patterns in large data sets. The actual data mining task is the automatic or semiautomatic analysis of large quantities of data to extract previously unknown interesting patterns such as groups of data records i.e.cluster analysis, unusual records (anomaly detection) and dependencies association rule mining. This usually involves using databa...

Databases today are ranging in size into the Tera Bytes. It is an information extraction activity whose goal is to discover hidden facts contained in databases. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Major Data Mining Tasks and processes include Classification, Clustering, Associations, Vi...

Data mining is an important paradigm for educational assessment. The usual assumption is that mining is performed after educational activity with that activity having been designed without regard for the mining process. This paper discusses how the prospects for successful mining can be improved by imposing constraints or biases on the activities and instruments that generate the data. These bi...

one of the most important issues related to knowledge discovery is the field of comment mining. opinion mining is a tool through which the opinions of people who comment about a specific issue can be evaluated in order to achieve some interesting results. this is a subset of data mining. opinion mining can be improved using the data mining algorithms. one of the important parts of opinion minin...

one of the most important steps involved in mining operations is to select an appropriate extraction method for mine resources. after choosing the extraction method, it is usually impossible to replace it with another one because it may be so expensive that implementation of the entire project could be economically impossible. choosing a mining method depends on the geological and geometrical c...

Incremental workflow mining is a technique for automatically deriving a process model from the on-going executions of a process. This way, the process model becomes more and more accurate, and is automatically adapted when the process is being changed. Therefore, incremental workflow mining could help in flexible workflow support: In this paper, we describe a setting that combines incremental w...