Open AccessA SURVEY ON DEEP LEARNING FOR THE DETECTION OF THE INAPPROPRIATE CONTENT PRESENT IN TEXT
Author(s) -
Shivakumar H Teli,
Kiran Kiran
Publication year - 2021
Publication title -
international journal of engineering applied science and technology
Language(s) - English
Resource type - Journals
ISSN - 2455-2143
DOI - 10.33564/ijeast.2021.v06i04.046
Subject(s) - filter (signal processing) , harm , hatred , annoyance , computer science , content (measure theory) , web survey , information retrieval , world wide web , internet privacy , psychology , social psychology , mathematics , political science , mathematical analysis , politics , law , computer vision , loudness
certain piece of textual information producedby any user or agent is said to be inappropriate if theexpressed intent can cause hate, annoyance to other usersor exhibits lack of respect, rudeness, which isdisrespectful towards certain individuals or communitieswho may cause harm to oneself or others. In the presentday scenario the different classification techniques areused to filter this kind of annoying text or messages. Andbrowsers this days should be able to filter such kind ofsearches done in the searching engines which will be doneevery day. Providing such classification technique to filtersuch messages or searches which are not appropriateusing some of the deep learning algorithms andconsidering the web search conversations such kind ofsearches which is found as abusive or which might causehatred can be eliminated.