Column concept determination based on multiple evidences

Summary Tables on the web provide rich information. To make sufficient usage of web tables, the semantics of columns should be identified correctly. The absence, misspelling, and abbreviation in column names bring the challenges in column semantics identification. Facing this challenge, we extract m...

Full description

Saved in:
Bibliographic Details
Published inConcurrency and computation Vol. 33; no. 8
Main Authors An, Xianxi, You, Sihan, Guo, Ziyang, Lu, Zeguang, Zheng, Bo, Shi, Shengfei, Song, Yan
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc 25.04.2021
Subjects
Algorithms
data integration
Feature extraction
Matching
Semantics
structure feature
Tables (data)
text feature
web table
Online AccessGet full text

Cover

More Information
Summary:Summary Tables on the web provide rich information. To make sufficient usage of web tables, the semantics of columns should be identified correctly. The absence, misspelling, and abbreviation in column names bring the challenges in column semantics identification. Facing this challenge, we extract multiple features including keywords, concepts, and structure from the content in the column. Thus, we could identify the column semantics by matching these multiple features. For the extraction and matching with these features, we propose efficient algorithms. Experimental results on real data sets show that our solution achieves high performance.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.5457