DocumentCode :
2000067
Title :
A Multi-Strategy Approach to Rating and Filtering Online Resources
Author :
Bertino, Elisa ; Ferrari, Elena ; Perego, Andrea ; Zarri, Gian Piero
Author_Institution :
Purdue Univ., West Lafayette, IN
fYear :
2005
fDate :
26-26 Aug. 2005
Firstpage :
519
Lastpage :
523
Abstract :
This paper illustrates some of the semantic Web techniques used in the framework of the EU project EUFORBIA, which deals with the rating and filtering of `questionable´ Web sites concerned with racism, violence, pornography, etc. The rationale for using a high-level semantic approach in this domain is linked with the assumption that an in-depth description of the `semantic content´ of Web sites should allow the implementation of filtering strategies more flexible, accurate and (neatly) sophisticated than the current ones. From a technical point of view, the final result of the project consists of two integrated prototypes that communicate through a common ontology
Keywords :
information filtering; meta data; ontologies (artificial intelligence); semantic Web; EUFORBIA project; Web filtering; Web site; high-level semantic approach; multistrategy approach; online resource; semantic Web technique; Educational institutions; Information filtering; Information filters; Knowledge representation; Libraries; Ontologies; Protection; Prototypes; Semantic Web; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Database and Expert Systems Applications, 2005. Proceedings. Sixteenth International Workshop on
Conference_Location :
Copenhagen
ISSN :
1529-4188
Print_ISBN :
0-7695-2424-9
Type :
conf
DOI :
10.1109/DEXA.2005.21
Filename :
1508325
Link To Document :
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