
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.
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Taxonomy
TopicsTopic Modeling · Authorship Attribution and Profiling · Natural Language Processing Techniques
