Corroborate and learn facts from the web
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Language-Independent Set Expansion of Named Entities Using the Web
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
The YAGO-NAGA approach to knowledge discovery
ACM SIGMOD Record
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A probabilistic model of redundancy in information extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
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In this paper, we want to show which difficulties arise when automatically constructing a domain-independent knowledge base from the web. We show possible applications for such a knowledge base to emphasize its importance. Current knowledge bases often use manually-built patterns for extraction and quality assurance which does not scale well. Our contribution to the community will be a technique to automatically assess extracted information to ensure high quality of the information and a method of how the knowledge base can be kept up to date. The research builds upon the existing WebKnox system for Web Knowledge Extraction which is able to extract named entities and facts from the web. This is a position paper.