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Articles by P. Senthil Pandian
Total Records ( 2 ) for P. Senthil Pandian
  P. Senthil Pandian , K. Karthikeyan and K.N. Sivabalan
  Enormous amount of informationís are gathered and viewed through world wide web by different users. The user practices their views by entering hypertext credentials by internet with a large repository of web pages and web usage mining process is essential for efficient web site management, personalization, business and support services and network traffic flow analysis, etc., web page contains images, text, videos and other multimedia and web log file holds the information of the user accesses in the websites. The log file shall have some noisy and ambiguous data which may affect the data mining process and large quantity of web traffic should be handled effectively to acquire desired information. So the log file should be preprocessed to improve the quality of data. Preprocessing consists of data cleaning and data filtering, user identification and session identification. Two sets of log files are collected and processed to obtain experimental results. This study presents a framework for user and session preprocessing and clustering with Hidden Damage Data algorithm (HDD) and also analyzes the navigational behavior of users through an enhanced Conviction Frequent Pattern Mining Algorithm (CFPMA) to identify frequent patterns in web log data. The experimental result shows that the proposed technique achieves low execution time and higher accuracy when compared with the other existing methods.
  M. Muthukumar , P. Senthil Pandian and K. Karthikeyan
  In the current digital age, volume of data is getting increased by 59% on every year worldwide. According to research, it is estimated that 70-85% of data is unstructured and more than 20% performance degradation happens due to improper database design. There are many factors which may influence the performance of the database among the factors a data type plays an important role. Choosing the right data type for each column is most essential in either heavy transaction or less transaction tables. Proper database design provides multiple benefits like minimized disk usage, less consumptions of CPU and resources and improved query performance. The proper usage of data types in the database improves the performance of the whole system. These data types are of different types and should be used in an intelligent way to achieve the expected behavior. This study demonstrates how to choose the correct data types to design efficient database and also identifies which data type should be used or not to be used.
 
 
 
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