With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...

In recent years, due to the expansion of financial institutions,as well as the popularity of the World Wide Weband e-commerce, a significant increase in the volume offinancial transactions observed. In addition to the increasein turnover, a huge increase in the number of fraud by user’sabnormality is resulting in billions of dollars in lossesover the world. T...

OLAP mining is a mechanism which integrates on-line analytical processing (OLAP) with data mining so that mining can be performed in diierent portions of databases or data warehouses and at diierent levels of abstraction at user's nger tips. With rapid developments of data warehouse and OLAP technologies in database industry, it is promising to develop OLAP mining mechanisms. With our years of ...

The pattern mining community has shifted its attention from local pattern mining to pattern set mining. The task of pattern set mining is concerned with finding a set of patterns that satisfies a set of constraints and often also scores best w.r.t. an optimisation criteria. Furthermore, while in local pattern mining the constraints are imposed at the level of individual patterns, in pattern set...

Social harmony problems are being existed in social system, which is an open giant complex system. For solving such kind of problems the Metasynthesis system approach proposed by Qian XS et al will be applied. In this approach the data, information, knowledge, model, experience and wisdom should be integrated and synthesized. Data mining, text mining and web mining are good techniques for using...

The article describes the basic principles and methods of Data mining and Process mining, their similarities and differences. The authors examine the research in Educational Data Mining field, associated with the use of Data mining techniques in education, give examples of problems to be solved with the use of Data mining and Process mining techniques in the area of traditional and e-learning, ...

Novel data-mining tasks in e-science involve mining of distributed, highly heterogeneous data and knowledge sources. However, standard data mining platforms, such as Weka and Orange, involve only their own data mining algorithms in the process of knowledge discovery from local data sources. In contrast, next generation data mining technologies should enable processing of distributed data source...

An accepted trend is to categorize web mining into three main areas: web content mining, web structure mining and web usage mining. Web content mining involves extracting details/information from the contents of webpages and performing things like knowledge synthesis. Web structure mining involves the usage of graph theory to understand website structure/hierarchy. Web usage mining involves the...

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Data mining is a non-trivial process. That is identifying novel, valid and potentially useful patterns in data. Data mining supports automatic data exploration. That is extracting hidden information from the huge database. Data mining refers to search useful and relevant information from the database. Spatial mining is a branch of data mining. The spatial mining deals with the location or geo-r...