The BINGO! Focused Crawler: from Bookmarks to Archetypes Sergej Sizov, Stefan Siersdorfer, Martin Theobald, and Gerhard Weikum   View Paper (PDF)   Return to Demonstrations Abstract The BINGO! system implements an approach to focused crawling that aims to overcome the limitations of the initial training data. To this end, BINGO! identifies, among the crawled and positively classified documents of a topic, characteristic "archetypes" and uses them for periodically re-training the classifier; this way the crawler is dynamically adapted based on the most significant documents seen so far. Two kinds of archetypes are considered: good authorities as determined by employing Kleinberg's link analysis algorithm, and documents that have been automatically classified with high confidence using a linear SVM classifier DiSC'03 © 2003 Association for Computing Machinery