Retrieval of personal Web documents by extracting subjective expressions

Takahiro Hayashi*, Koji Abe, Rikio Onai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a method for gathering Japanese web documents which contain personal opinions. Our method is available as a pre-processing of applications for mining various opinions. In order to find personal documents on the Web, we focus on four kinds of subjective expressions: (1) negative meaning expressions, (2) final particles, (3) interjections, and (4) specific symbols such as face marks. Measuring the frequencies of these subjective expressions in a document, our method classifies web documents into personal and non-personal ones. Besides, our method gives the documents scores which show the accuracy of the classification results. We experimentally confirmed the effectiveness of the proposal using 1200 web documents. The experimental results have shown the precision and recall of the proposed classification are 0.70 and 0.87, respectively. In addition, we have confirmed that personal documents can be easily obtained by gathering documents which are given high scores.

Original languageEnglish
Title of host publicationProceedings - 22nd International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINA 2008
Pages1187-1192
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event22nd International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINA 2008 - Gino-wan, Okinawa
Duration: 2008 Mar 252008 Mar 28

Other

Other22nd International Conference on Advanced Information Networking and Applications Workshops/Symposia, AINA 2008
CityGino-wan, Okinawa
Period08/3/2508/3/28

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint

Dive into the research topics of 'Retrieval of personal Web documents by extracting subjective expressions'. Together they form a unique fingerprint.

Cite this