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 :
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