Web Extraction

Web extraction focuses on automatically extracting structured information from web pages and documents, aiming to transform unstructured or semi-structured data into usable formats for various applications. Current research emphasizes developing robust models that leverage diverse features, including textual content, hypertext attributes (e.g., font styles), and even visual information from page layouts, often employing neural network architectures like Transformers and Mixture of Experts to improve accuracy and efficiency. This field is crucial for building knowledge graphs, powering search engines, and enabling data-driven applications across numerous domains, with recent work highlighting the importance of large-scale datasets and label-efficient training methods to overcome data scarcity and annotation challenges.