（様式）FY2021 Annual Report for International Joint ResearchInternational Joint Digital Archiving Center for Japanese Art and Culture (ARC-iJAC),Art Research Center, Ritsumeikan University〔International Joint Research to Utilize the Center's Facilities and Equipment〕
Date (2023/01/04):
1. Title of the research project“Natural Language Processing for a Geospatial Exploration of Japanese Ukiyo-e Prints”
2. Research leader
Name

Organization and title

Ewa Machotka

Stockholm University, Dept. of Asian and Middle
Eastern Studies, Associate Professor

3. Co-researcher (Total： 5persons)NameOrganization and title

Ryo Akama

Ritsumeikan University, Professor

John Pavlopoulos

Stockholm University,, Affiliated Researcher

Panagiotis Papapetrou

Stockholm University, Professor

Konstantina Liagkou

Athens Technology Center, Research Assistant

Marita Chatzipanagiotou(member until December 2021)

Athens University of Economics and Business, Research Assistant

4. Overview of the research project (about 150 words). Note: If you have changed your project since the time ofapplication submission, please write clearly where you made changes.
The proposed project aims at a large-scale digital geospatial exploration of places depicted in Japanese early modern
ukiyo-e landscape prints, and focuses on a dataset of prints accessible through the Ukiyo-e Portal Database hosted
by the ARC. The first stage of the project, which is still ongoing, focuses on the extraction of information on thedepicted locations by applying the Natural Language Processing (NLP) technology (e.g. Named Entity
Recognition) on their meta-data; and their subsequent geolocation on the map of Japan in order to identify, mapand contextualize the frequency and distribution of places in the cultural history of the first half of the 19th c. The
second stage of the project, which is planned in the near future, will concern visual analysis of the images performed
with the use of neural encoders (pre-trained to classify/caption generic images) to explore feasibility oficonographical identification of these places and involved challenges related to artistic mediation linked to theprocess of their visual representation. Overall, these analyses will generate a new information on geo-temporal
distribution of the culturally significant sites and their visual depiction contributing to a better understanding ofJapanese landscape prints in general.

（様式）5. Overview of the research results.

Note: We may use this section for the Center’s PR.

The first stage of our exploratory mixed-method analysis of the places depicted in Japanese early modern prints
featuring meisho (lit. famous places) has so far delivered promising results as well as opened up new
methodological and conceptual pathways to realize our overall research goals aiming at a large-scale geospatial
study of landscape images in Japan. First, by employing the NLP approaches such as transfer-learning and Named
Entity Recognition (NER) and applying our fine-tuned recognition model on a large dataset of prints, we
provided a use-case of how a macroanalysis (or so-called ‘distant viewing’) of a visual dataset can be successfully
undertaken in the context of art historical research of Japanese early modern visual culture. We also identified anumber of methodological challenges related to this mixed-method analysis rooted in the complexities of theJapanese early-modern writing system, problems with adequate identification of historical place names, andspecificities of pre-modern printed medium. Second, we developed “Ukiyo-e Distant Viewer”, an online
application for geolocation of the automatically recognised places on the map of Japan, that enables explorationof frequency and spatial distribution of these places across the map and identification of culturally significant
places at a given time period. Third, we used the visualised outcome to perform an error analysis and compared
our ML-based NER with gazetteer-based approaches. Our analysis also opened up new research pathways via theapplication of historical gazetteers. Furthermore, we also experimented with Optical Character Recognition(OCR), in order to investigate the following hypothesis: could the automatically recognised (not humantranscribed) text be used to extract place named-entities in order to increase the scale of our study? Answering
this research question has a wide significance (beyond our study) especially considering a large amount ofJapanese early-modern textual materials (also pervading visual culture) that still remain un-transcribed, and theirsubsequent limited accessibility for a general public. Hence, with this study we outlined the path for future
research that will bring us closer to the understanding of early-modern landscape images and Japanese culture atlarge.
6. Research activities

Note: We may use this section for the Center’s PR.

(1) Books(2) Articles:● “Distant Viewing of Ukiyo-e Prints.” 2022. The Proceedings of the 13th Conference on Language
Resources and Evaluation (LREC 2022): 5879–5888. Machotka E., Pavlopoulos J., and Liagkou K. Peerreviewed.
● ”Automated Recognition of Geographical Named Entities in Titles of Ukiyo-e prints.” Association for
Computing Machinery (2021): 70–77. Machotka, E. Pavlopoulos, J., and Chatzipanagiotou, M. Peerreviewed.
(3) Presentations:●“Mapping meisho: NLP for Japanese Art History”, December 2022, International Conference “The Digital
Turn in Early Modern Japanese Studies”, University of Cambridge. Presenters: Machotka E., Pavlopoulos
J., Liagkou K.

●“Mapping Japanese Landscape Prints with NLP: Challenges and Solutions”, November 2022, International
Workshop “Error Correcting HTR for Historical Manuscripts”, Ca’Foscari University of Venice.
Presenters: Machotka E., Pavlopoulos J., Liagkou K.

●"HTR Error Correction: An Overview of the Recent HTREC Challenge", November 2022. International
Workshop “Error Correcting HTR for Historical Manuscripts”, Ca’Foscari University of Venice. Presenter:Pavlopoulos J.

●”Improving Named-Entity Recognition on titles of Ukiyo-e prints: Towards a ‘Distant Viewing’ in ArtHistory”, July 2022, Digital Humanities Conference 2022 (ADHO) Responding to Asian Diversity, Tokyo.
Presenters: Machotka, E. Pavlopoulos, J., Liagkou K. Peer-reviewed.

●“Distant Viewing of Ukiyo-e Prints.” June 2022, The 13th Language Resources and Evaluation Conference(LREC), Marseilles. Presenters: Machotka E., Pavlopoulos J. Liagkou K. Peer-reviewed.

●“Automated Harvesting of Geospatial Data from Ukiyo-e Prints with NLP”, February 2022, Annual Report
Meeting, The International Joint Digital Archiving Center for Japanese Art and Culture, Ritsumeikan
University, Kyoto, Presenters: Machotka E., Pavlopoulos J.

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”Automated Recognition of Geographical Named Entities in Titles of Ukiyo-e prints”, December 2021,
Digital Humanities Workshop (DHW 2021), Kiev, Presenters: Machotka, E. Pavlopoulos, J.,
Chatzipanagiotou, M. Peer-reviewed.

(4) Symposiums and/or research meeting you organized:●“International Workshop “Error Correcting HTR for Historical Manuscripts”, Ca’Foscari University ofVenice, November 2022, Participants no.: 16 speakers. Organizers and chairs: Machotka E. andPavlopoulos J., Organizing Institutions: Center for Digital and Public Humanities at the Ca’Foscari
University of Venice, and Stockholm University.

(5) Other research activities (Lectures to the general public, and appearances in/contributions to mass media)(6) Academic awards(7) Grants-in-Aid for Scientific Research -KAKENHI(8) Competitive grants other than KAKENHI●“Strategic Research Funding” of the Board of Human Sciences, Stockholm University(9) Other achievements