scholarly journals An Early Decision Algorithm to Accelerate Web Content Filtering

2006 ◽  
pp. 833-841 ◽  
Author(s):  
Po-Ching Lin ◽  
Ming-Dao Liu ◽  
Ying-Dar Lin ◽  
Yuan-Cheng Lai
Keyword(s):  
Web Content ◽  
Content Filtering ◽  
Decision Algorithm ◽  
Early Decision

scholarly journals Accelerating Web Content Filtering by the Early Decision Algorithm

2008 ◽  
Vol E91-D (2) ◽  
pp. 251-257 ◽  
Author(s):  
P.-C. LIN ◽  
M.-D. LIU ◽  
Y.-D. LIN ◽  
Y.-C. LAI
Keyword(s):  
Web Content ◽  
Content Filtering ◽  
Decision Algorithm ◽  
Early Decision

A General Framework for Web Content Filtering

2009 ◽  
Vol 13 (3) ◽  
pp. 215-249 ◽  
Author(s):  
Elisa Bertino ◽  
Elena Ferrari ◽  
Andrea Perego
Keyword(s):  
General Framework ◽  
Web Content ◽  
Content Filtering

Web Content Filtering

2006 ◽  
pp. 112-132 ◽  
Author(s):  
Elisa Bertino ◽  
Elena Ferrari ◽  
Andrea Perego
Keyword(s):  
Social Issues ◽  
Public Information ◽  
Research Area ◽  
Web Pages ◽  
Online Information ◽  
Web Content ◽  
Content Filtering ◽  
Web Technologies ◽  
Harmful Content ◽  
Conceptual Hierarchies

The need to filter online information in order to protect users from possible harmful content can be considered as one of the most compelling social issues derived from the transformation of the Web into a public information space. Despite that Web rating and filtering systems have been developed and made publicly available quite early, no effective approach has been established so far, due to the inadequacy of the proposed solutions. Web filtering is then a challenging research area, needing the definition and enforcement of new strategies, considering both the current limitations and the future developments of Web technologies—in particular, the upcoming Semantic Web. In this chapter, we provide an overview of how Web filtering issues have been addressed by the available systems, bringing in relief both their advantages and shortcomings, and outlining future trends. As an example of how a more accurate and flexible filtering can be enforced, we devote the second part of this chapter to describing a multi-strategy approach, of which the main characteristics are the integration of both list- and metadata-based techniques and the adoption of sophisticated metadata schemes (e.g., conceptual hierarchies and ontologies) for describing both users’ characteristics and Web pages content.

scholarly journals Advanced Quantum Based Neural Network Classifier and Its Application for Objectionable Web Content Filtering

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 98069-98082
Author(s):  
Om Prakash Patel ◽  
Neha Bharill ◽  
Aruna Tiwari ◽  
Vikram Patel ◽  
Ojas Gupta ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Network Classifier ◽  
Web Content ◽  
Content Filtering

An intelligent categorization engine for bilingual web content filtering

2005 ◽  
Vol 7 (6) ◽  
pp. 1183-1190 ◽  
Author(s):  
P.Y. Lee ◽  
S.C. Hui ◽  
A.C.M. Fong
Keyword(s):  
Web Content ◽  
Content Filtering

XFighter: an intelligent web content filtering system

Kybernetes ◽  
2009 ◽  
Vol 38 (9) ◽  
pp. 1541-1555 ◽  
Author(s):  
A.C.M. Fong ◽  
S.C. Hui ◽  
P.Y. Lee
Keyword(s):  
Web Content ◽  
Content Filtering
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