Functional Classification of Web Pages with Deep Learning

Balim, Caner; Özkan, Kemal

doi:10.1109/siu.2019.8806240

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Cited by 4 publications

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“…Balim and Özkan [13], a deep learning based model was proposed for functional classification of web pages, regardless of language. The authors used Transfer Learning to reduce the cost during the feature extraction process from recorded web page images.…”

Section: Related Workmentioning

confidence: 99%

A Hybrid Approach for Web Pages Classification

Hioual¹,

Hemam²,

Hioual³

et al. 2022

ISI

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Currently, the internet is growing at an exponential rate and can cover just some required data. However, the immense amount of web pages makes the discovery of the target data more difficult for the user. Therefore, an efficient method to classify this huge amount of data is essential where web pages can be exploited to their full potential. In this paper, we propose an approach to classify Web pages based on their textual content. This approach is based on an unsupervised statistical technique (TF-IDF) for keyword extraction (textual content) combined with a supervised machine learning approach, namely recurrent neural networks.

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Section: Related Workmentioning

confidence: 99%