For pursuing PhD in the domain of data mining, one should first narrow down a topic and then conduct the corresponding research to become a doctorate. Therefore, we will explore the latest topics in data mining and also talk about:
- How to prepare synopsis?
- How to go about implementation in data mining? What tools to select?
- What to include in thesis writing?
- Fraud app detection by using sentimental analysis:
- Stock market analysis and prediction
- Customer behavior prediction using web usage mining
- Smart Health Consulting Project
- Web Data Mining To Detect Online Spread Of Terrorism
- Finance analysis (Stock prediction, customer behavior prediction etc.)
Synopsis is the initial document that has to be submitted to the university, and only upon its acceptance, you can further your investigation. Make sure that your synopsis includes:
The innovative idea/method proposed by you in the synopsis should then be implemented in an authorized tool to determine its value and efficiency. Generally MATLAB is preferred for data mining applications as it can extract huge amount of data from the web. Some of the other tools suggested for data mining are given as follows,
WEKA is a JAVA based customization tool. This tool includes predictive analysis and modelling techniques, clustering, regression and classification.
Python is a quite popular tool because of its prevailing features. Orange is an open source tool which is written in python with necessary data analytics, text analysis, and machine learning features.
Rapid Miner is an open source tool which provides advanced analytics. It incorporates multifaceted mining functions like data pre-processing, visualization, and predictive analysis.
After implementation, you need to prepare your Thesis/Dissertation that highlights your complete research work. It will include 5 to 6 chapters which are Introduction, Literature Review, Proposed methodology, Design and Implementation, Results and Conclusion.
In case you think we have missed something, please comment below your valuable suggestions!