Volume 13, Number 4

Text Advertisements Analysis using Convolutional Neural Networks


Abdulwahed Almarimi and Asmaa Salem, Bani Waleed University, Libya


In this paper, we describe the developed model of the Convolutional Neural Networks CNN to a classification of advertisements. The developed method has been tested on both texts (Arabic and Slovak texts).The advertisements are chosen on a classified advertisements websites as short texts. We evolved a modified model of the CNN, we have implemented it and developed next modifications. We studied their influence on the performing activity of the proposed network. The result is a functional model of the network and its implementation in Java and Python. And analysis of model results using different parameters for the network and input data. The results on experiments data show that the developed model of CNN is useful in the domains of Arabic and Slovak short texts, mainly for some classification of advertisements. This paper gives complete guidelines for authors submitting papers for the AIRCC Journals.


Convolutional neural networks, advertisement text, back-propagation algorithm, classification, encoding of text.