Web-scale table census and classification

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Abstract
We report on a census of the types of HTML tables on the Web according to a fine-grained classification taxonomy describing the semantics that they express. For each relational table type, we describe open challenges for extracting from them semantic triples, i.e., knowledge. We also present TabEx, a supervised framework for web-scale HTML table classification and apply it to the task of classifying HTML tables into our taxonomy. We show empirical evidence, through a large-scale experimental analysis over a crawl of the Web, that classification accuracy significantly outperforms several baselines. We present a detailed feature analysis and outline the most salient features for each table type.