This paper proposes integration of a social network with the tripartite model of ontologies by P. Mika. That model is based on three dimensions, i.e. actors, concepts and instances, and illustrates ontology emergence using actor-concept and conceptinstance relations. However, another important ingredient is the actor-actor relation. For example, a vocabulary is sometimes shared within a community, which consists of dense relations among persons. Through considering of who knows whom (as described in FOAF) and who collaborates with whom, the extracted ontology might be improved. We propose an advanced model based on Mika’s work, and describe a case study using the model. We show an application of an extracted ontology for information recommendation for academic conferences.
%0 Generic
%1 hamasaki2007ontology
%A Hamasaki, Masahiro
%A Matsuo, Yutaka
%A Nisimura, T.
%B International Workshop on Semantic Web for Collaborative Knowledge Acquisition (SWECKA2007)
%D 2007
%K ol_web2.0 data_socialnetworks
%T Ontology Extraction using Social Network
%U http://staff.aist.go.jp/masahiro.hamasaki/index-e.html
%X This paper proposes integration of a social network with the tripartite model of ontologies by P. Mika. That model is based on three dimensions, i.e. actors, concepts and instances, and illustrates ontology emergence using actor-concept and conceptinstance relations. However, another important ingredient is the actor-actor relation. For example, a vocabulary is sometimes shared within a community, which consists of dense relations among persons. Through considering of who knows whom (as described in FOAF) and who collaborates with whom, the extracted ontology might be improved. We propose an advanced model based on Mika’s work, and describe a case study using the model. We show an application of an extracted ontology for information recommendation for academic conferences.
@misc{hamasaki2007ontology,
abstract = {This paper proposes integration of a social network with the tripartite model of ontologies by P. Mika. That model is based on three dimensions, i.e. actors, concepts and instances, and illustrates ontology emergence using actor-concept and conceptinstance relations. However, another important ingredient is the actor-actor relation. For example, a vocabulary is sometimes shared within a community, which consists of dense relations among persons. Through considering of who knows whom (as described in FOAF) and who collaborates with whom, the extracted ontology might be improved. We propose an advanced model based on Mika’s work, and describe a case study using the model. We show an application of an extracted ontology for information recommendation for academic conferences.},
added-at = {2011-02-17T17:42:21.000+0100},
author = {Hamasaki, Masahiro and Matsuo, Yutaka and Nisimura, T.},
biburl = {https://www.bibsonomy.org/bibtex/2fad2913a06c8cb158a69a80e3dcbdecd/dbenz},
booktitle = {International Workshop on Semantic Web for Collaborative Knowledge Acquisition (SWECKA2007)},
description = {Masahiro Hamasaki},
file = {hamasaki2007ontology.pdf:hamasaki2007ontology.pdf:PDF},
groups = {public},
interhash = {4a452a28251de436b241f42ee3ac9c32},
intrahash = {fad2913a06c8cb158a69a80e3dcbdecd},
keywords = {ol_web2.0 data_socialnetworks},
timestamp = {2013-07-31T15:39:42.000+0200},
title = {Ontology Extraction using Social Network},
url = {http://staff.aist.go.jp/masahiro.hamasaki/index-e.html},
username = {dbenz},
year = 2007
}