Comparison of Word Representation Method for Obscene Language Removal

Student: Kotov Georgiy

Supervisor: Ekaterina Artemova

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 7

Year of Graduation: 2016

This work is devoted to comparison of different text representation models for obscene language removal. To test these models we collect and mark up a collection of texts, published on lurkmore web site. To compare the models we estimate their precision and recall and the latter is viewed as a more important measure than the latter. The highest recall is achieved by using the annotated suffix tree model. There are a few applications of obese language removal, such as parental controls or tools for editors of online content.

Full text (added May 30, 2016)

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