CoVA: Context-aware Visual Attention for Webpage Information Extraction
Anurendra Kumar, Keval Morabia, William Yang Wang, Kevin Chen–Chuan Chang, Alex Schwing · 2022
Webpage information extraction (WIE) is an important step to create knowledge bases.For this, classical WIE methods leverage the Document Object Model (DOM) tree of a website.However, use of the DOM tree poses significant challenges as context and appearance are encoded in an abstract manner.To address this challenge we propose to reformulate WIE as a context-aware Webpage Object Detection task.Specifically, we develop a Contextaware Visual Attention-based (CoVA) detection pipeline which combines appearance features with syntactical structure from the DOM tree.To study the approach we collect a new large-scale dataset 1 of e-commerce websites for which we manually annotate every web element with four labels: product price, product title, product image and others.On this dataset we show that the proposed CoVA approach is a new challenging baseline which improves upon prior state-of-the-art methods.