Extracting Relevant Snippets from Web Documents through Language Model based Text Segmentation
10.1109/wi.2007.115 , 10.1109/wi.2007.69 , 10.1109/wi.2007.79 , 10.1109/wi.2007.56 , 10.1109/wi.2007.4427180 , 10.1109/wi.2007.154 , 10.1109/wi.2007.122 , 10.1109/wi.2007.118 , 10.1109/wi.2007.24 , 10.1109/wi.2007.4427196 , 10.1109/wi.2007.9 , 10.1109/wi.2007.49 , 10.1109/wi.2007.4427178 , 10.1109/wi.2007.23 , 10.1109/wi.2007.4427167 , 10.1109/wi.2007.39 , 10.1109/wi.2007.142 , 10.1109/wi.2007.106 , 10.1109/wi.2007.103 , 10.1109/wi.2007.35 , 10.1109/wi.2007.17 , 10.1109/wi.2007.13 , 10.1109/icdcs.2008.115 , 10.4230/dagsemproc.08091.16
10.1109/wi.2007.115 , 10.1109/wi.2007.69 , 10.1109/wi.2007.79 , 10.1109/wi.2007.56 , 10.1109/wi.2007.4427180 , 10.1109/wi.2007.154 , 10.1109/wi.2007.122 , 10.1109/wi.2007.118 , 10.1109/wi.2007.24 , 10.1109/wi.2007.4427196 , 10.1109/wi.2007.9 , 10.1109/wi.2007.49 , 10.1109/wi.2007.4427178 , 10.1109/wi.2007.23 , 10.1109/wi.2007.4427167 , 10.1109/wi.2007.39 , 10.1109/wi.2007.142 , 10.1109/wi.2007.106 , 10.1109/wi.2007.103 , 10.1109/wi.2007.35 , 10.1109/wi.2007.17 , 10.1109/wi.2007.13 , 10.1109/icdcs.2008.115 , 10.4230/dagsemproc.08091.16
Extracting Relevant Snippets from Web Documents through Language Model based Text Segmentation
We present a framework for media interpretation that leverages low-level information extraction to a higher level of abstraction in order to support semantics-based information retrieval for the Semantic Web. The overall goal of the framework is to provide high-level content descriptions of documents for maximizing precision and recall of semantics-based information retrieval.
- Nottingham Trent University United Kingdom
- State University of New York at Potsdam United States
- French National Centre for Scientific Research France
- Karlsruhe Institute of Technology Germany
- University of Chicago United States
330, Economics, User Profiles, [INFO.EIAH] Computer Science [cs]/Technology for Human Learning, Web Data Mining, info:eu-repo/classification/ddc/330, context-aware, ddc:330, Added values; Document ranking; Domain ontologies, scenarios, 004, Information Filtering, Pattern Taxonomic Model, ddc: ddc:004
330, Economics, User Profiles, [INFO.EIAH] Computer Science [cs]/Technology for Human Learning, Web Data Mining, info:eu-repo/classification/ddc/330, context-aware, ddc:330, Added values; Document ranking; Domain ontologies, scenarios, 004, Information Filtering, Pattern Taxonomic Model, ddc: ddc:004
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