Papers

4

Total Citations

21

H-Index

2

About

Dr. Mitali Srivastava is a leading researcher in the field of Web Usage Mining, with a specialized focus on scalable data preprocessing and robot detection. Her work addresses the critical challenge of analyzing massive, unstructured web server logs to extract meaningful user navigation patterns. Dr. Srivastava’s major contributions include the development of a MapReduce-based user identification algorithm (2018, 9 citations), which efficiently handles the growing volume of web data by leveraging parallel processing. She further advanced the field with a performance evaluation of parallel preprocessing techniques that incorporate robot detection approaches (2021, 8 citations), ensuring that only genuine human behavior is analyzed. Her most recent work, the IRPDP_HT2 method (2023), introduces a scalable data preprocessing solution using Hadoop MapReduce, pushing the boundaries of efficiency in web usage mining. Additionally, her analysis of robot detection approaches (2017, 2 citations) provides a crucial framework for distinguishing ethical from unethical web robots, addressing both security and bandwidth concerns. With over 20 citations across her key publications, Dr. Srivastava’s research is foundational for students and practitioners seeking to harness big data technologies for understanding user behavior on the web.

Research Focus

Key Achievements

2
H-Index
4
Papers
21
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
A MapReduce-Based User Identification Algorithm in Web Usage Mining
9 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Banaras Hindu University, Dehradun Institute of Technology University

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago