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» Automatic Wrappers for Large Scale Web Extraction
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KDD
2002
ACM
170views Data Mining» more  KDD 2002»
14 years 9 months ago
Web site mining: a new way to spot competitors, customers and suppliers in the world wide web
When automatically extracting information from the world wide web, most established methods focus on spotting single HTMLdocuments. However, the problem of spotting complete web s...
Martin Ester, Hans-Peter Kriegel, Matthias Schuber...
NAR
2010
119views more  NAR 2010»
13 years 3 months ago
3V: cavity, channel and cleft volume calculator and extractor
As larger macromolecular structures become available, there is a growing need to understand their `internal' volumes--such as deep clefts, channels and cavities--as these oft...
Neil Voss, Mark Gerstein
CIKM
2009
Springer
14 years 3 months ago
Semi-supervised learning of semantic classes for query understanding: from the web and for the web
Understanding intents from search queries can improve a user’s search experience and boost a site’s advertising profits. Query tagging via statistical sequential labeling mode...
Ye-Yi Wang, Raphael Hoffmann, Xiao Li, Jakub Szyma...
LREC
2008
153views Education» more  LREC 2008»
13 years 10 months ago
Linguistically Light Lexical Extensions for Ontologies
An increasing number of enterprises are beginning to include semantic web ontologies into their Information Extraction (IE) and Text Analytics (TA) applications. This can be chall...
Brian Davis, Siegfried Handschuh, Alexander Trouss...
WWW
2002
ACM
14 years 9 months ago
Searching with numbers
A large fraction of the useful web comprises of specification documents that largely consist of hattribute name, numeric valuei pairs embedded in text. Examples include product in...
Rakesh Agrawal, Ramakrishnan Srikant