Paper Info
Title
Hybrid approach to extracting information from web-tables
Abstract
This study concerns the extracting of information from tables in HTML documents. In our previous work, as a prerequisite for information extraction from tables in HTML, algorithms for separating meaningful tables and decorative tables were constructed, because only meaningful tables can be used to extract information and a preponderant proportion of decorative tables in training harms the learning result. In order to extract information, this study separated the head from the body in meaningful tables by extending the head extraction algorithm that was constructed in our previous work, using a machine learning algorithm, C4.5, and set up heuristics for table-schema extraction from meaningful tables by analyzing their head(s). In addition, table information in triples was extracted by determining the relation between the data and the extracted table schema. We obtained 71.2% accuracy in extracting table-schemata and information from the meaningful tables.
Year
DOI
Venue
2006
10.1007/11940098_11
ICCPOL
Keywords
Field
DocType
table schema,table-schema extraction,study concern,hybrid approach,meaningful table,html document,decorative table,previous work,head extraction algorithm,table information,information extraction,text mining,machine learning
Computer science,Information extraction,Heuristics,Artificial intelligence,Natural language processing,Web tables,Information schema,HTML,Schema (psychology),Table (information),The Internet
Conference
Volume
ISSN
ISBN
4285
0302-9743
3-540-49667-X
Citations 
PageRank 
References 
3
0.48
6
Authors
3
Name
Order
Citations
PageRank
Sungwon Jung132059.65
Mi-Young Kang24011.87
Hyuk-Chul Kwon313629.02