A method of extraction and visualisation for relationships among objects on web

Authors:
Kazuhiro Morita;Takuki Ogawa;Hiroya Kitagawa;Masao Fuketa;Jun-ichi Aoe
Affiliations:
Information Solution, Institute of Technology and Science, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, Japan;Information Solution, Institute of Technology and Science, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, Japan;Information Solution, Institute of Technology and Science, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, Japan;Information Solution, Institute of Technology and Science, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, Japan;Information Solution, Institute of Technology and Science, The University of Tokushima, 2-1, Minami-josanjima, Tokushima, Japan
Venue:
International Journal of Intelligent Systems Technologies and Applications
Year:
2013

Citing 5
Cited 0

Finding authoritative people from the web

Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
POLYPHONET: An advanced social network extraction system from the Web

Web Semantics: Science, Services and Agents on the World Wide Web
Extracting Social Networks Among Various Entities on the Web

ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Extracting word sets with non-taxonomical relation

ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Extraction, selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary

Knowledge and Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Relations with other objects are sure to exist in one object such as the persons, things and the enterprises. The structure related to these objects is called a social network. In recent years, the extraction of object relationships using web corpora is researched to visualise a social network. This paper aims to extract object relationships including the direction of the relation considering context information. In the proposal method, related words that are objects related to the object given as an input word are acquired at first. And object relationships between an input word and each related word are extracted. Moreover, the system that visualises related words and the object relationships as a correlation diagram is implemented. From the experiment for extraction of object relationships, the accuracy of the correct answer rate of 80% or more, was obtained by using the proposal method.