Document verification using n-grams and histograms of words

Almarimi, Abdulwahed; Andrejková, Gabriela; Sedmak, Peter

doi:10.1109/informatics.2015.7377801

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2016

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“…An introduction to study the method we did in [12], here we show a new final evaluation using distances. Let -T is divided into a sequence of coherent text parts, T = ⟨T 1 , T 2 .…”

Section: Histograms Of Wordsmentioning

confidence: 99%

Dissimilarities Detections in Texts Using Symbol n-grams and Word Histograms

Andrejková

Almarimi

2016

Open Computer Science

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Texts (books, novels, papers, short messages) are sequences of sentences, words or symbols. Each author has an unique writing style. It can be characterized by some collection of attributes obtained from texts. The text verification is the case of an authorship verification where we have some text and we analyze if all parts of this text were written by the same (unknown or known) author. In this paper, there are analyzed and compared results of two developed methods for a text verification based on ngrams of symbols and on local histograms of words. The results of a symbol n-gram method and a method of word histograms for a dissimilarities searching in text parts of each text are analyzed and evaluated. The searched dissimilarities call for an attention to the text (or not) if the text parts were written by the same author or not. The attention depends on selected parameters prepared in experiments. Results illustrate usability of the methods to dissimilarities searching in text parts.

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“…An introduction to study the method we did in [12], here we show a new final evaluation using distances. Let -T is divided into a sequence of coherent text parts, T = ⟨T 1 , T 2 .…”

Section: Histograms Of Wordsmentioning

confidence: 99%