Information extraction from HTML pages and its integration

Author

Itai, Kumi ; Takasu, Atsuhiro ; Adachi, Jun

Author_Institution

Univ. of Tokyo, Japan

fYear

2003

Firstpage

276

Lastpage

281

Abstract

We propose a method for transforming HTML tables that have different structures into a common XML list structure and integrating them. This integration enables us to browse and compare all information in separate HTML pages uniformly. This paper focuses on the tasks of information extraction from tables and its data categorization. For this purpose, we compare three algorithms: (I) data classification using a support vector machine, (II) table structure estimation and data categorization using a hidden Markov model, and (III) data classification by the combination of a support vector machine and hidden Markov model. Finally, we report the experimental results.

Keywords

Internet; classification; hidden Markov models; hypermedia markup languages; information retrieval; learning automata; HTML pages; HTML tables; common XML list structure; data categorization; data classification; hidden Markov model; information browsing; information extraction; support vector machine; table structure estimation; Data mining; HTML; Hidden Markov models; Informatics; Internet; Personal communication networks; Scheduling; Support vector machine classification; Support vector machines; XML;

fLanguage

English

Publisher

ieee

Conference_Titel

Applications and the Internet Workshops, 2003. Proceedings. 2003 Symposium on

Print_ISBN

0-7695-1873-7

Type

conf

DOI

10.1109/SAINTW.2003.1210172

Filename

1210172