Assoc Prof Dr. Arunesh Krishna Pillai - Web Usage Mining - Excellence in Research 🏆 

Early Academic Pursuits

He embarked on his academic journey with a strong foundation in computer science, driven by a passion for exploring the realms of data mining and web analytics. Graduating with a Ph.D. in Computer Science from Bharathidasan University, Trichy, his research interests gravitated towards the intersection of technology and human behavior, particularly in the domain of web usage mining.

Professional Endeavors

His professional trajectory spans over decades of dedicated service in academia. As the Dean and Associate Professor of Computer Science at Sri. S R N M College, Tamil Nadu, he has been instrumental in shaping the educational landscape, imparting knowledge and fostering critical thinking among students. His leadership role has been marked by a commitment to excellence and innovation, guiding both faculty and students towards academic and research excellence.

Contributions and Research Focus in Web Usage Mining

His research focus revolves around leveraging web usage mining techniques to enhance user experience and optimize website performance. His seminal projects, such as the "Web Mining Approach to the Recommender Systems Based on Usage Behavior," exemplify his dedication to advancing the field of data mining and computational intelligence. By developing innovative models like Rank measure Recommendations (RANK-RECO) and Testing measure Recommendations (TEST-RECO), he has demonstrated the potential of statistical solutions in analyzing and evaluating web systems, particularly in decision-making applications.

Accolades and Recognition

His contributions to the field of web usage mining have earned him accolades and recognition from both academia and industry. His projects funded by esteemed institutions like the University Grants Commission (UGC) underscore the significance of his research endeavors in addressing real-world challenges and driving technological innovation. His commitment to excellence in teaching and research has also been acknowledged by his peers and students, further solidifying his reputation as a visionary leader in the field.

Impact and Influence

His research has had a profound impact on the field of web analytics and user behavior analysis, influencing decision-making processes and shaping the digital landscape. By developing data mining approaches to path profile analysis and recommender systems, he has contributed to the advancement of educational systems and e-commerce platforms alike. His insights into user behavior and website optimization strategies have empowered organizations to make informed decisions and enhance user engagement, ultimately driving business growth and success.

Legacy and Future Contributions

Notable Publications

• Map Reduce for big data processing based on traffic aware partition and aggregation
• Analysing soil data using data mining classification techniques
• ID3 decision tree classification: An algorithmic perspective based on error rate
• Unsupervised Binary BAT algorithm based Network Intrusion Detection System using enhanced multiple classifiers
• Models for recommender systems in web usage mining based on user ratings
• Text Mining: Text Similarity measure for news articles based on string-based approach
• Content-based image retrieval using statistical parameters of a medical image
• Analysis of brain MRI images for Tumor segmentation using Fuzzy C means Algorithm
• Role of decision tree classification in data mining
• Agricultural soil lime status analysis using data mining classification techniques
• Feature analysis of recommender techniques employed in the recommendation engines