Web Table Extraction, Retrieval and Augmentation: A Survey
February 01, 2020 ยท The Cartographer ยท ๐ ACM Transactions on Intelligent Systems and Technology
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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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