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In the data-driven world, the importance of data analytics is ever-changing to conceive a great impact on data mining. Data mining recognizes patterns and establishes interconnection on a huge dataset through data analysis. The promising applications of data mining are financial data analysis, market-basket analysis, biological data analytics, intrusion detection, fraud detection, telecommunication industry. retail industry, recommender systems, and disease detection.
A varied set of domains utilized in data mining is time-series data mining, web mining, temporal data mining, spatial data mining, tempo-spatial data mining, educational data mining, business, medical, science, and engineering. Multimedia data mining, online data mining, spatial and spatiotemporal data mining, scientific data mining, symbolic data mining, geospatial contrast mining, architecture conscious data mining, and sustainable mining are the utmost advanced concepts in data mining. Unification, scalability, and optimization of data mining algorithms, cube-oriented multidimensional data mining, and scalable real-time mining are challenging research areas of data mining that require more consideration in future development.
The existing PHD thesis in data mining broadly contributes various challenging applications, future scopes, and trending research gaps. This list of topics has immense potential for PHD thesis and research in data mining.
