ClueWeb22: 10 Billion Web Documents with Visual and Semantic Information
This dataset addresses the need for a high-quality, large-scale web corpus for academic and industry research, offering previously industry-only signals at scale to the research community.
The authors introduced ClueWeb22, a dataset of 10 billion web pages with visual and semantic information, designed to support research in areas like information systems and AI by providing a larger, higher-quality, and more varied corpus compared to previous versions.
ClueWeb22, the newest iteration of the ClueWeb line of datasets, provides 10 billion web pages affiliated with rich information. Its design was influenced by the need for a high quality, large scale web corpus to support a range of academic and industry research, for example, in information systems, retrieval-augmented AI systems, and model pretraining. Compared with earlier ClueWeb corpora, the ClueWeb22 corpus is larger, more varied, of higher-quality, and aligned with the document distributions in commercial web search. Besides raw HTML, ClueWeb22 includes rich information about the web pages provided by industry-standard document understanding systems, including the visual representation of pages rendered by a web browser, parsed HTML structure information from a neural network parser, and pre-processed cleaned document text to lower the barrier to entry. Many of these signals have been widely used in industry but are available to the research community for the first time at this scale.