Open AccessFull Content-based Web Page Classification Methods by using Deep Neural Networks
Author(s) -
Suleyman Suleymanzade,
Fargana J. Abdullayeva
Publication year - 2021
Publication title -
statistics, optimization and information computing
Language(s) - English
Resource type - Journals
eISSN - 2311-004X
pISSN - 2310-5070
DOI - 10.19139/soic-2310-5070-1056
Subject(s) - computer science , web page , news aggregator , classifier (uml) , information retrieval , artificial neural network , artificial intelligence , web mining , data mining , machine learning , world wide web
The quality of the web page classification process has a huge impact on information retrieval systems. In this paper, we proposed to combine the results of text and image data classifiers to get an accurate representation of the web pages. To get and analyse the data we created the complicated classifier system with data miner, text classifier, and aggregator. The process of image and text data classification has been achieved by the deep learning models. In order to represent the common view onto the web pages, we proposed three aggregation techniques that combine the data from the classifiers.