Shrish Verma

Papers

Total Citations

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About

Shrish Verma is a leading researcher in web analytics and cybersecurity, with a focused expertise in distinguishing human browsing behavior from automated software agents, or web robots. His work is pivotal for organizations seeking to extract genuine knowledge from web server logs, ensuring that data-driven decisions reflect actual visitor engagement rather than bot interference. Verma’s most-cited paper, “Agglomerative Approach for Identification and Elimination of Web Robots from Web Server Logs to Extract Knowledge about Actual Visitors” (2015, 34 citations), introduced an innovative ensemble-based learning framework that significantly improves robot session identification through multi-fold labeling and comparative analysis of bagging and boosting methods. Complementing this, his study “A Comparative Analysis of Browsing Behavior of Human Visitors and Automatic Software Agents” (2015, 13 citations) provides an exhaustive investigation of resource acquisition trends, hourly activity patterns, and entry-exit behaviors, offering a granular understanding of bot versus human navigation. Together, these contributions have shaped modern approaches to web log cleansing and behavioral analytics, with his methodologies cited by researchers tackling spam detection, user experience optimization, and server security. Verma’s work remains essential for anyone aiming to filter noise from web data and uncover authentic user insights.