Open AccessBayesian methods for classification inappropriate web pages
Author(s) -
Jorge Armando Rodríguez,
Jenny P. Ortiz
Publication year - 2018
Publication title -
visión electrónica/visión electrónica
Language(s) - English
Resource type - Journals
eISSN - 2248-4728
pISSN - 1909-9746
DOI - 10.14483/22484728.14626
Subject(s) - computer science , web page , naive bayes classifier , the internet , tree (set theory) , filter (signal processing) , task (project management) , process (computing) , representation (politics) , data mining , web content , machine learning , information retrieval , artificial intelligence , world wide web , engineering , computer vision , mathematical analysis , mathematics , systems engineering , politics , support vector machine , law , political science , operating system
The incursion of the Internet has created new forms of information and communication, but it can also carry great dangers, when its use is related to inappropriate content, such as, access to harmful contents and the rise of new kinds of crimes. In this situation, automatic filtering systems identify improper Internet content. This paper describes the use of an algorithm, to automatically filter out inappropriate Web pages. To accomplish this (automatic filtering) task implementation method TAN (Tree Augmented Naive Bayes) is plasma. Data mining algorithms and computational learning for the extraction process, representation and classification of web pages are implemented.