Web Table Extraction, Retrieval and Augmentation: A Survey

February 01, 2020 ยท The Cartographer ยท ๐Ÿ› ACM Transactions on Intelligent Systems and Technology

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
Survey/review paper โ€” maps the landscape rather than implementing a method.

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"Title-pattern auto-detect: Web Table Extraction, Retrieval and Augmentation: A Survey"

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Authors Shuo Zhang, Krisztian Balog arXiv ID 2002.00207 Category cs.IR: Information Retrieval Citations 61 Venue ACM Transactions on Intelligent Systems and Technology Last Checked 1 day ago
Abstract
Tables are a powerful and popular tool for organizing and manipulating data. A vast number of tables can be found on the Web, which represents a valuable knowledge resource. The objective of this survey is to synthesize and present two decades of research on web tables. In particular, we organize existing literature into six main categories of information access tasks: table extraction, table interpretation, table search, question answering, knowledge base augmentation, and table augmentation. For each of these tasks, we identify and describe seminal approaches, present relevant resources, and point out interdependencies among the different tasks.
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