There is a tremendous increase in the research of data mining. Data mining is the process of extraction of data from large database. Knowledge Discovery in database (KDD) is another name of data mining. Privacy protection has become a necessary requirement in many data mining applications due to emerging privacy legislation and regulations. One of the most important topics in research community...

There is an emerging interest in optimisation strategies for distributed data mining in order to improve response time. Optimisation techniques operate by first identifying factors that affect the performance in distributed data mining, computing/assigning a “cost” to those factors for alternate scenarios or strategies and then choosing a strategy that involves the least cost. In this paper we ...

Vaidya, Jaideep Shrikant. Ph.D., Purdue University, August, 2004. Privacy Preserving Data Mining over Vertically Partitioned Data. Major Professor: Chris Clifton. The goal of data mining is to extract or “mine” knowledge from large amounts of data. However, data is often collected by several different sites. Privacy, legal and commercial concerns restrict centralized access to this data. Theore...

Discovering knowledge from raw data is one of the goals of data mining. Yet, it is not always clear how this knowledge is used in educational computing systems and how exactly it is integrated with other knowledge like the pedagogy used. We present a case study where the use of the data mining results was initially described, to a large degree, at the implementation level, thus largely ignoring...

One of the biggest challenges that higher learning institutions face today is to improve the quality of managerial decisions. The managerial decision making process becomes more complex as the complexity of educational entities increase. Educational institute seeks more efficient technology to better manage and support decision making procedures or assist them to set new strategies and plan for...

Text mining refers to the process of discovering interesting and non trivial patterns or knowledge embedded in unstructured text documents from a fixed domain. It is also known as knowledge discovery from text databases. Text mining tasks include text categorization, text clustering, concept/entity extraction, document summarization and entity relation modelling. Extracting concept/fact from th...

Data mining and Knowledge discovery has several important application areas. Data mining and knowledge discovery have been topics considered at many AI, database and statistical conferences. Knowledge discovery generally refers to the process of identifying valid, novel and understandable patterns. Knowledge discovery from large databases, often called data mining, refers to the application of ...

Web Data Mining is an important area of Data Mining which deals with the extraction of interesting knowledge from the World Wide Web. It defines the application of data mining techniques to extract knowledge from web data, including web documents, hyperlinks between documents, usage logs of web sites, etc. Therefore, the process of extracting useful information from the contents of web document...

Data Mining is the process of examining the information from different point of view and compressing it for the relevant data. This data can also be utilized to build the incomes. Data Mining is also known as Data or Knowledge Discovery. The basic purpose of data mining is to search patterns which have minimal user inputs and efforts. Data Mining plays a very crucial role in the various fields....

Data mining is a process of discovery of relationship, patterns and knowledge from data. The emergence of network-based cluster computing environment has created a natural demand for scalable techniques of data mining that can be exploit the full benefit of such environments. In this paper, we described system architecture for scalable and portable data mining architecture for clustered environ...