Sansung Kim

Korea Advanced Institute of Science and Technology

Papers

Total Citations

H-Index

About

Sang-Sung Kim is a researcher whose work bridges the gap between web information retrieval and data mining, with a particular focus on enhancing the efficiency of focused web crawlers. His most notable contribution, detailed in his highly cited 2019 paper "An effective approach to enhancing a focused crawler using Google," presents a novel methodology that leverages the Google search engine to significantly improve the precision and relevance of topic-specific crawling. This work, which has garnered 13 citations, demonstrates his ability to integrate existing large-scale search infrastructure with targeted crawling algorithms, offering a practical solution for researchers and practitioners seeking to collect domain-specific web data more effectively. Kim’s research addresses a critical challenge in the age of information overload: how to efficiently filter and retrieve only the most pertinent content from the vast expanse of the internet. By combining theoretical insights with real-world application, his work has provided a valuable framework for subsequent studies in focused crawling and web mining. His contributions are particularly relevant for those developing specialized search tools, digital libraries, and competitive intelligence systems, marking him as a thoughtful innovator in the field of web information systems.