Discover: a resource discovery system based on content routing
Proceedings of the Third International World-Wide Web conference on Technology, tools and applications
Web Meta-search using Unsupervised Neural Networks
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
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With the explosive growth of the Web, one of the biggest challenges in exploiting the wealth of available information is to locate the relevant documents. Search engines play a crucial role in addressing this problem by precompiling a large index of available information to quickly produce a set of possibly relevant documents in response to a query. While most Web users make extensive use of the Internet search engines, few people have more than a vague idea of how these systems work. This installment of "Trends & Controversies" features two essays that describe the inner workings of Internet search engines. In the first, Michael Mauldin, who developed Lycos, presents a brief history of Web search services and describes how search engines such as Lycos perform their tasks. In the second, Erik Selberg and Oren Etzioni, who developed the MetaCrawler Softbot, describe how their system exploits the results from other search engines to provide a comprehensive set of documents in response to a query.驴Craig Knoblock, Editor