Name
Abstract | ||
|---|---|---|
Keeping people away from litigious information becomes one of the most important research area in network information security. Indeed, Web filtering is used to prevent access to undesirable Web pages. In this paper we review some existing solutions, then we propose a violent Web content detection and filtering system called "WebAngels filter" which uses textual and structural analysis. "WebAngels filter" has the advantage of combining several data-mining algorithms for Web site classification. We discuss how the combination learning based methods can improve filtering performances. Our preliminary results show that it can detect and filter violent content effectively. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-72588-6_126 | International Conference on Computational Science (3) |
Keywords | Field | DocType |
web site classification,litigious information,combining classifiers,webangels filter,undesirable web page,violent web content detection,data-mining algorithm,web violent content detection,important research area,existing solution,network information security,violent content,information security,structure analysis,categorical data,data mining,web pages | Data mining,Web mining,Web intelligence,Web page,Information retrieval,Web analytics,Web mapping,Computer science,Data Web,Social Semantic Web,Web content | Conference |
Volume | ISSN | Citations |
4489 | 0302-9743 | 3 |
PageRank | References | Authors |
0.41 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Radhouane Guermazi | 1 | 23 | 5.55 |
| Mohamed Hammami | 2 | 181 | 30.54 |
| Abdelmajid Ben Hamadou | 3 | 353 | 56.16 |