The weighted majority algorithm
Information and Computation
Detecting Tables in HTML Documents
DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
Flexible Web Document Analysis for Delivery to Narrow-Bandwidth Devices
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Mining tables from large scale HTML texts
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Logical structure analysis: From HTML to XML
Computer Standards & Interfaces
Extracting logical structures from HTML tables
Computer Standards & Interfaces
Mining for attributes and values in tables
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
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The TABLE tags in HTML (Hypertext Markup Language) documents are widely used for formatting layout of Web documents as well as for describing genuine tables with relational information. As a prerequisite for information extraction from the Web, this paper presents an efficient method for sophisticated table detection. The proposed method consists of two phases: preprocessing and attribute-value relations extraction. During preprocessing, a part of genuine or non-genuine tables are filtered out using a set of rules, which are devised based on careful examination of general characteristics of various HTML tables. The remaining tables are detected at the attribute-value relations extraction phase. Specifically, a value area is extracted and checked out whether there is syntactic coherency. Furthermore, the method looks for semantic coherency between an attribute area and a value area of a table. Experimental results with 11,477 TABLE tags from 1393 HTML documents show that the method has performed better compared with previous works, resulting in a precision of 97.54% and a recall of 99.22%.