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A Review of Data Mining for Clustering Applications and Machine Intelligence

Rüdiger Wirth, Jochen Hipp


Data mining is a technique in which appropriate information is extracted from raw data. Data mining is used to perform various tasks such as clustering, prediction analysis and association rule generation with the support of various data mining tools and techniques. In data mining methodologies, clustering is the most efficient technique that can be used to extract useful information from raw data. Clustering is a technique in which similar and different types of data can be clustered to consider useful information from the data set. The clustering is of many forms like density-based clustering, hierarchical clustering, and partitioning based clustering. Data mining is a technique for examining large preceding databases in order to generate new information which helps us to decide future trends. It also helps to find a unique pattern and vital knowledge from the existing database. This study reveals the limitations and benefits of the various clustering methodologies.


Knowledge Discovery in Database, Information Forecast, Machine Learning and Neural Networks, Clustering in Data Mining.

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