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» Unsupervised Relation Extraction From Web Documents
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PVLDB
2008
141views more  PVLDB 2008»
13 years 7 months ago
WebTables: exploring the power of tables on the web
The World-Wide Web consists of a huge number of unstructured documents, but it also contains structured data in the form of HTML tables. We extracted 14.1 billion HTML tables from...
Michael J. Cafarella, Alon Y. Halevy, Daisy Zhe Wa...
WWW
2005
ACM
14 years 8 months ago
Thresher: automating the unwrapping of semantic content from the World Wide Web
We describe Thresher, a system that lets non-technical users teach their browsers how to extract semantic web content from HTML documents on the World Wide Web. Users specify exam...
Andrew Hogue, David R. Karger
ACL
2011
12 years 11 months ago
Knowledge-Based Weak Supervision for Information Extraction of Overlapping Relations
Information extraction (IE) holds the promise of generating a large-scale knowledge base from the Web’s natural language text. Knowledge-based weak supervision, using structured...
Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke S....
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning from multi-topic web documents for contextual advertisement
Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
AAAI
2010
13 years 5 months ago
A Topic Model for Linked Documents and Update Rules for its Estimation
The latent topic model plays an important role in the unsupervised learning from a corpus, which provides a probabilistic interpretation of the corpus in terms of the latent topic...
Zhen Guo, Shenghuo Zhu, Zhongfei Zhang, Yun Chi, Y...