Can Japanese Manga Be Automatically Classified from Public Library Holdings?

Masaki Eto; Teru Agata; Noriko Sugie; Yasuharu Otani; Mari Agata

doi:10.1109/JCDL.2017.7991593

Can Japanese Manga Be Automatically Classified from Public Library Holdings?

Masaki Eto, Teru Agata, Noriko Sugie, Yasuharu Otani, Mari Agata

Department of Library and Information Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This study addressed the automatic classification of Japanese manga held by public libraries. Holdings of 4,681 public libraries and similar facilities were investigated, and 29,795 manga titles were identified. Hierarchical clustering was applied to 631 titles that were each held by more than one hundred libraries. Five clusters were identified in the upper hierarchy. Principal coordinate analysis and a manual examination of individual titles were performed to identify the common characteristics of the works in each cluster. The results suggest that the proposed method offers a novel approach to large-scale classification of manga titles.

Original language	English
Title of host publication	2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538638613
DOIs	https://doi.org/10.1109/JCDL.2017.7991593
Publication status	Published - 2017 Jul 25
Event	17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 - Toronto, Canada Duration: 2017 Jun 19 → 2017 Jun 23

Publication series

Name	Proceedings of the ACM/IEEE Joint Conference on Digital Libraries
ISSN (Print)	1552-5996

Other

Other	17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017
Country/Territory	Canada
City	Toronto
Period	17/6/19 → 17/6/23

Keywords

hierarchical clustering
manga
public libraries

ASJC Scopus subject areas

Engineering(all)

Access to Document

10.1109/JCDL.2017.7991593

Cite this

Eto, M., Agata, T., Sugie, N., Otani, Y., & Agata, M. (2017). Can Japanese Manga Be Automatically Classified from Public Library Holdings? In 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 [7991593] (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/JCDL.2017.7991593

Can Japanese Manga Be Automatically Classified from Public Library Holdings? / Eto, Masaki; Agata, Teru; Sugie, Noriko et al.

2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7991593 (Proceedings of the ACM/IEEE Joint Conference on Digital Libraries).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Eto, M, Agata, T, Sugie, N, Otani, Y & Agata, M 2017, Can Japanese Manga Be Automatically Classified from Public Library Holdings? in 2017 ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017., 7991593, Proceedings of the ACM/IEEE Joint Conference on Digital Libraries, Institute of Electrical and Electronics Engineers Inc., 17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017, Toronto, Canada, 17/6/19. https://doi.org/10.1109/JCDL.2017.7991593

@inproceedings{8aee7bfdecdf4f38811ee37b274d3feb,

title = "Can Japanese Manga Be Automatically Classified from Public Library Holdings?",

abstract = "This study addressed the automatic classification of Japanese manga held by public libraries. Holdings of 4,681 public libraries and similar facilities were investigated, and 29,795 manga titles were identified. Hierarchical clustering was applied to 631 titles that were each held by more than one hundred libraries. Five clusters were identified in the upper hierarchy. Principal coordinate analysis and a manual examination of individual titles were performed to identify the common characteristics of the works in each cluster. The results suggest that the proposed method offers a novel approach to large-scale classification of manga titles.",

keywords = "hierarchical clustering, manga, public libraries",

author = "Masaki Eto and Teru Agata and Noriko Sugie and Yasuharu Otani and Mari Agata",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 17th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2017 ; Conference date: 19-06-2017 Through 23-06-2017",

year = "2017",

month = jul,

day = "25",

doi = "10.1109/JCDL.2017.7991593",

language = "English",

series = "Proceedings of the ACM/IEEE Joint Conference on Digital Libraries",