A major obstacle to effective searching and indexing in the era of the explosion of information is the sheer volume of web content. The extensive indexing and retrieval techniques of traditional web search engines frequently prevent them from providing domain-specific, relevant results. In order to improve the effectiveness of searching and indexing, this dissertation investigates the creation and application of domain-specific web document clustering. Thorough tests will be used to evaluate the suggested system by contrasting domain-specific clustering’s performance with that of conventional search and indexing techniques. To assess the efficacy and efficiency of the clustering strategy, metrics like computational efficiency, precision, recall, and F1 score will be used. The study is anticipated to produce notable improvements in search relevancy and speed within particular topics, providing users with a more targeted and effective search experience. Furthermore, this study’s discoveries may help improve information retrieval systems and lay the groundwork for more domain-specific online document clustering research in future. By bridging the gap between specialized information needs and general-purpose search engines, this dissertation seeks to improve the usability and accessibility of domain-specific information.