Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
The "DGX" distribution for mining massive, skewed data
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Network arts: exposing cultural reality
Proceedings of the 13th international World Wide Web conference on Alternate track papers & posters
Distributed search over the hidden web: hierarchical database sampling and selection
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Methods for domain-independent information extraction from the web: an experimental comparison
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Table extraction using spatial reasoning on the CSS2 visual box model
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Rules of thumb for information acquisition from large and redundant data
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
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Information on the Web is not only abundant but also redundant. This redundancy of information has an important consequence on the relation between the recall of an information gathering system and its capacity to harvest the core information of a certain domain of knowledge. This paper provides a new idea for estimating the necessary Web coverage of a knowledge acquisition system in order to achieve a certain desired coverage of the contained core information.