Title
Entity answer extraction of web table
Abstract
This paper presents an entity answer extraction method based on list web table. Firstly, extract table from page using the features of web page table and label, segment the table that includes the potential entity answers by calculating the relevance of web table's title and query context, merge the table elements of each column according to table properties, and merge the web table's title with the merged elements of column again. Secondly, using merged passage as context of entity recognition, and recognize the entity for each element of the table, thus get the probability of the column elements belongs to the same type of entity answer, and locate the passages of entity answers and the entity answers. Finally, we conduct the experiment in the task of Entity Track of TREC2009. It turns out that the proposed method shows a very good result, the accuracy of entity answer extraction for web table has achieved 99.08%.
Year
DOI
Venue
2010
10.1109/FSKD.2010.5569791
FSKD
Keywords
Field
DocType
table passage segment,web table title,web table,web page table,information retrieval,query context,entity answer extraction,web sites,table entity answer extraction,entity recognition,table ner,list answers,web pages,feature extraction,data mining,accuracy,machine learning
Decision table,Information retrieval,Web page,Computer science,Feature extraction,Web tables,Merge (version control),Single Table Inheritance,Text recognition
Conference
Volume
ISBN
Citations 
5
978-1-4244-5931-5
0
PageRank 
References 
Authors
0.34
9
5
Name
Order
Citations
PageRank
Yangbo Xu1161.81
Zhengtao Yu246069.08
Cunli Mao35111.54
Yasheng Wang403.38
Jianyi Guo52010.99