In this section, we briefly outline the major issues in data mining research, partitioning them into five groups: mining methodology, user interaction, efficiency and scalability, diversity of data types, and data mining and society..
Data mining is a big area of data sciences, which aims to discover patterns and features in data, often large data sets.
It includes regression, classification, clustering, detection of anomaly, and others.
It also includes preprocessing, validation, summarization, and ultimately the making sense of the data sets..
Some data-mining applications that include medical data are anomaly detection, audience prediction, banking, bioinformatics, crime investigation, customer segmentation, disease diagnosis, electric load prediction, financial data forecasting, fraud detection, lie detection, product design and manufacturing, product .
Data mining is a big area of data sciences, which aims to discover patterns and features in data, often large data sets.
It includes regression, classification, clustering, detection of anomaly, and others.
It also includes preprocessing, validation, summarization, and ultimately the making sense of the data sets..
Data mining techniques and tools enable enterprises to predict future trends and make more-informed business decisions.
Data mining is a key part of data analytics overall and one of the core disciplines in data science, which uses advanced analytics techniques to find useful information in data sets..
Data mining is a big area of data sciences, which aims to discover patterns and features in data, often large data sets.
It includes regression, classification, clustering, detection of anomaly, and others.
It also includes preprocessing, validation, summarization, and ultimately the making sense of the data sets..
Data mining is the process of searching and analyzing a large batch of raw data in order to identify patterns and extract useful information.
Companies use data mining software to learn more about their customers.
It can help them to develop more effective marketing strategies, increase sales, and decrease costs..
In this section, we briefly outline the major issues in data mining research, partitioning them into five groups: mining methodology, user interaction, efficiency and scalability, diversity of data types, and data mining and society..
The needs of the business and federal communities have helped to direct the growth of data mining research
For example, typical applications in data mining include the following: Use of historical financial records on bank customers to predict good and bad credit risks
Use of sales records and customer demographics to perform market segmentation
Following is the list of latest topics in data mining for final year project, thesis, and research: Web mining is an application of data mining for discovering data patterns from the web
Web mining is of three categories – content mining, structure mining and usage mining
Content mining detects patterns from data collected by the search engine
Currently, there are various research and thesis topics in Data Mining
Masters students can choose from these topics for their final year project
Ph D research topics in data mining are also available hereFollowing are the topics under data mining to study:
