DocumentCode
3323976
Title
Extracting Loosely Structured Data Records Through Mining Strict Patterns
Author
Wu, Yipu ; Chen, Jing ; Li, Qing
Author_Institution
Dept. of Comput. Sci., City Univ. of Hong Kong, Hong Kong
fYear
2008
fDate
7-12 April 2008
Firstpage
1322
Lastpage
1324
Abstract
Extracting loosely structured data records (DRs) has wide applications in many domains, such as forum pattern recognition, blog data analysis, and books and news review analysis. Currently existing methods work well for strongly structured DRs only. In this paper, we address the problem of extracting loosely structured DRs through mining strict patterns. In our method, we utilize both content feature and tag tree feature to recognize the loosely structured DRs, and propose a new approach to extract the DRs automatically. Through experimental study we demonstrate that this method is both effective and robust in practice.
Keywords
data mining; pattern recognition; blog data analysis; loosely structured data records; news review analysis; pattern recognition; strict pattern mining; tag tree feature; Application software; Computer science; Data mining; HTML; Information services; Internet; Pattern recognition; Videos; Web pages; Web sites;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering, 2008. ICDE 2008. IEEE 24th International Conference on
Conference_Location
Cancun
Print_ISBN
978-1-4244-1836-7
Electronic_ISBN
978-1-4244-1837-4
Type
conf
DOI
10.1109/ICDE.2008.4497543
Filename
4497543
Link To Document