Donghwan Bae

Korea Advanced Institute of Science and Technology

Papers

Total Citations

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About

Donghwan Bae is a researcher in information retrieval and web crawling, with a particular focus on enhancing the efficiency and accuracy of focused web crawlers. His most-cited work, "An effective approach to enhancing a focused crawler using Google" (2019), has garnered 13 citations, demonstrating its relevance in the field. In this study, Bae proposed a novel method that leverages Google’s search capabilities to improve the precision of focused crawlers, which are essential for domain-specific data collection. By integrating external search engine results, his approach reduces irrelevant page downloads and increases the relevance of crawled content, addressing a key challenge in web mining. This contribution is particularly valuable for applications in academic research, competitive intelligence, and personalized content aggregation. Bae’s work stands out for its practical, scalable solution that bridges traditional crawling techniques with modern search engine APIs, offering a cost-effective alternative to more complex machine learning methods. His research continues to influence the development of more intelligent and resource-efficient web crawling systems, making him a notable figure in the ongoing evolution of information retrieval technologies.