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On extracting data from tables that are encoded using HTML
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AI
DOI：10.1016/j.knosys.2019.105157.png)
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摘要
En 中文
Tables are a common means to display data in human-friendly formats. Many authors have worked on proposals to extract those data back since this has many interesting applications. In this article, we summarise and compare many of the proposals to extract data from tables that are encoded using HTML and have been published between 2000 and 2018. We first present a vocabulary that homogenises the terminology used in this field; next, we use it to summarise the proposals; finally, we compare them side by side. Our analysis highlights several challenges to which no proposal provides a conclusive solution and a few more that have not been addressed sufficiently; simply put, no proposal provides a complete solution to the problem, which seems to suggest that this research field shall keep active in the near future. We have also realised that there is no consensus regarding the datasets and the methods used to evaluate the proposals, which hampers comparing the experimental results. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
HTML documents
Web tables
Table mining
Data extraction
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期刊
K
IF:
7.6
论文数:
1.3W
被引数:
4.5W
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