Analysis of Conceptualization Patterns across Groups of People

Fumiko Kano Glückstad, Tue Herlau, Mikkel Nørgaard Schmidt, Morten Mørup, Rafal Rzepka, Kenji Araki

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

This paper analyzes patterns of conceptualizations possessed by different groups of subjects. The eventual goal of this work is to dynamically learn and structure semantic representations for groups of people sharing domain knowledge. In this paper, we conduct a survey for collecting data representing semantic representations of 34 subjects with different profiles in gender and educational background. The collected data is analyzed by an approach combining two extended versions of the Infinite Relational Model (Kemp et al. 2006) [1]: multiarray Infinite Relational Model (Mørup et al. 2010) [2] and normal Infinite Relational Model (Herlau et al. 2012) [3]. Results indicate that the employed approach not only localizes similar patterns of conceptualization within a group of subjects having a common profile, but also identifies differences in conceptualization across different subject groups.
Original languageEnglish
Title of host publication2013 Conference on Technologies and Applications of Artificial Intelligence
PublisherIEEE
Publication date2013
Pages349-354
ISBN (Print)978-1-4799-2528-5
Publication statusPublished - 2013
Event2013 Conference on Technologies and Applications of Artificial Intelligence (TAAI) - Taipei, Taiwan, Province of China
Duration: 6 Dec 20138 Dec 2013
http://taai2013.nccu.edu.tw/

Conference

Conference2013 Conference on Technologies and Applications of Artificial Intelligence (TAAI)
CountryTaiwan, Province of China
CityTaipei
Period06/12/201308/12/2013
Internet address

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