Automatic abstracting important sentences of web articles

Author

Ren, Fuji ; Li, Shigang ; Kita, Kenji

Author_Institution

Fac. of Eng., Tokushima Univ., Japan

Volume

3

fYear

2001

fDate

2001

Firstpage

1705

Abstract

Being increasingly popular, the Internet greatly changes our live. We can conveniently receive and send information via the Internet. With the information explosion in Web, it is becoming crucial to develop means to automatically extract important sentences from the Web articles. In this paper, we propose a method which uses both statistical and structural information in sentence extraction. In addition, following the analysis of human´s extractions, several heuristic rules are added to filter out non-important sentences and to prevent similar sentences from being extracted. Our experimental results proved the effectiveness of these means. In particular, once the heuristic rules being added, a significant improvement has been observed

Keywords

computational linguistics; information resources; information retrieval; natural languages; Internet; Web articles; heuristic rules; sentence extraction; statistical information; structural information; Data mining; Explosions; Frequency; Humans; Information filtering; Information filters; Internet; Production; Statistics; Surface reconstruction;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 2001 IEEE International Conference on

Conference_Location

Tucson, AZ

ISSN

1062-922X

Print_ISBN

0-7803-7087-2

Type

conf

DOI

10.1109/ICSMC.2001.973531

Filename

973531