@article{Zhang2020,

title = {Web Table Extraction, Retrieval, and Augmentation: A Survey},

author = {Shuo Zhang and Krisztian Balog},

url = {https://arxiv.org/pdf/2002.00207.pdf},

year  = {2020},

date = {2020-02-01},

journal = {ACM Transactions on Intelligent Systems and Technology (TIST)},

volume = {11},

number = {2},

pages = {1-35},

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.},

note = {Pre SFI},

keywords = {Table augmentation, Table extraction, Table interpretation, Table mining, Table retrieval, Table search, WP2: User Modeling Personalization and Engagement},

pubstate = {published},

tppubtype = {article}

}