Interstitial Content Detection

TL;DR

This paper explores methods to detect interstitial content on web pages using computer vision, aiming to create labeled datasets for machine learning applications.

Contribution

It introduces a novel approach combining computer vision techniques with exploratory research to identify interstitial content on websites.

Findings

Computer vision can effectively identify interstitials.

Potential for creating labeled datasets for ML.

Foundations for automated interstitial detection.

Abstract

Interstitial content is online content which grays out, or otherwise obscures the main page content. In this technical report, we discuss exploratory research into detecting the presence of interstitial content in web pages. We discuss the use of computer vision techniques to detect interstitials, and the potential use of these techniques to provide a labelled dataset for machine learning.