Hi sir, I need data mining seminar topic related with personalised web search.
Thanking You.
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Data mining technology is one of the fast growing technology that is used in credit card purchases, customer records, web site registrations and call record keeping. The results provided by data mining are used as a reference for researchers and business managers for analysis. Data mining is defined as sifting through very large amounts of data to obtain useful information. Some of the most important and popular data mining techniques are the rules of association, classification, grouping, prediction, and sequential patterns. Data mining techniques are used for a variety of applications. In the health care industry, data mining plays an important role in predicting disease. For detection of a disease, patient testing should be required. But with the data mining technique you should reduce the number of tests. This reduced test plays an important role in time and performance. This technique has advantages and disadvantages. This research examines how data mining techniques are used to predict different types of diseases. This article reviewed the research papers that focused mainly on the prediction of heart disease, diabetes and breast cancer.
Data Mining is the process of extracting hidden knowledge from large volumes of raw data. Knowledge must be new, not obvious, and one should be able to use it. Data mining has been defined as "the non-trivial extraction of previously unknown, implicit and potentially useful information from data." It is the science of extracting useful information from large databases. "It is one of the tasks in the process of Data mining is used to discover the knowledge of the data and present it in a way that is easily understood by humans.It is a process for examining large amounts of data collected routinely. Of data is more useful in an exploratory analysis because of nontrivial information in large volumes of data.It is a cooperative effort of humans and computers.The best results are achieved by balancing the knowledge of human experts in the description of Problems and goals with the search capabilities of computers.