# Web page classification with Google Image Search results

arXiv: https://arxiv.org/abs/2006.00226 · HTML: https://mlsanity.com/paper/2006.00226/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2020.

## Built on by (most cited first, 1 of 1)

- [Targeted and Troublesome: Tracking and Advertising on Children's Websites](https://mlsanity.com/paper/2308.04887/) (2023)

## Abstract (arXiv)

In this paper, we introduce a novel method that combines multiple neural network results to decide the class of the input. This is the first study which used the method for web pages classification. In our model, each element is represented by multiple descriptive images. After the training process of the neural network model, each element is classified by calculating its descriptive image results. We apply our idea to the web page classification problem using Google Image Search results as descriptive images. We obtained a classification rate of 94.90% on the WebScreenshots dataset that contains 20000 web sites in 4 classes. The method is easily applicable to similar problems.