New Functionality for Digital Libraries: Enhancing discoverability at the National Diet Library
| dc.audience | Audience::Information Technology Section | |
| dc.audience | Audience::Big Data Special Interest Group | |
| dc.audience | Audience::Knowledge Management Section | |
| dc.conference.sessionType | Knowledge Management with Information Technology and Big Data | |
| dc.conference.venue | Megaron Athens International Conference Centre (MAICC) | |
| dc.contributor.author | Satomi, Wataru | |
| dc.contributor.author | Aoike, Toru | |
| dc.contributor.author | Kawashima, Takanori | |
| dc.date.accessioned | 2025-09-24T09:13:35Z | |
| dc.date.available | 2025-09-24T09:13:35Z | |
| dc.date.issued | 2017 | |
| dc.description.abstract | The National Diet Library (NDL) is conducting research with the aim of developing next-generation digital libraries. As the result of the research until now, an experimental service called “Next Digital Library” (https://lab.ndl.go.jp/dl/) was opened to public from the NDL Laboratory Web site on March 29, 2019. The main purpose of the Next Digital Library is to verify the technical effectiveness of its full-text search function, automatic processing using machine learning, and the International Image Interoperability Framework (IIIF) API. In this paper, we explain new functionality for the Next Digital Library, namely full-text searches, image retrieval using automatic cutting of illustrations, whitening of digitized materials, automatic generation of table of contents for materials, automatic image processing for display on smartphones, and utilization of IIIF. | en |
| dc.identifier.citation | [1] Rafdi, M., Sarraf, A., Durrant, J., & Baker, J. British Library Machine Learning Experiment. Zenodo. http://doi.org/10.5281/zenodo.17168. (2015) [2] Chen, Liang-Chieh, et al. "Encoder-decoder with atrous separable convolution for semantic image segmentation." Proceedings of the European Conference on Computer Vision (ECCV). (2018). [3] Kiyonori Nagasaki et al. KuniDiCo Image Wall as a Base for Open Science: As an Example of leveraging of IIIF and Crowd4U. IPSJ SIG Technical Report (CH-112 No.3) pp.1-4. (2016) [4] Wataru Satomi, Toru Aoike, Takeshi Abekawa, Takanori Kawashima. Machine learning approaches for background whitening and contrast adjustment of digital images, Proceedings of the 8th Conference of Japanese Association for Digital Humanities, pp.157-160 (2018) [5] Toru Aoike, Wataru Satomi, Takanori Kawashima. Automatic extraction of illustration from images of documents and image retrieval. Proceeding of IPSJ SIG Computers and the Humanities’ pp.97-102 (2018) [6]Huang, Gao, et al. "Densely connected convolutional networks." Proceedings of the IEEE conference on computer vision and pattern recognition. (2017) [7] Iwasaki, Masajiro. "Pruned bi-directed k-nearest neighbor graph for proximity search." International Conference on Similarity Search and Applications. Springer, Cham, (2016) [8] Isola, Phillip, et al. "Image-to-image translation with conditional adversarial networks." Proceedings of the IEEE conference on computer vision and pattern recognition. (2017) [9] Chollet, François. "Xception: Deep learning with depthwise separable convolutions." Proceedings of the IEEE conference on computer vision and pattern recognition. (2017) [10] Liu, Wei, et al. "Ssd: Single shot multibox detector." European conference on computer vision. Springer, Cham, (2016) [11] Badrinarayanan, Vijay, Alex Kendall, and Roberto Cipolla. "Segnet: A deep convolutional encoder-decoder architecture for image segmentation." IEEE transactions on pattern analysis and machine intelligence 39.12, pp. 2481-2495(2017) | |
| dc.identifier.relatedurl | https://2019.ifla.org/ | |
| dc.identifier.uri | https://repository.ifla.org/handle/20.500.14598/6588 | |
| dc.language.iso | en | |
| dc.rights | Attribution 4.0 International | |
| dc.rights.accessRights | open access | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.keyword | Machine Learning | |
| dc.subject.keyword | Deep Learning | |
| dc.subject.keyword | full-text search | |
| dc.subject.keyword | IIIF | |
| dc.subject.keyword | next-generation digital libraries | |
| dc.title | New Functionality for Digital Libraries: Enhancing discoverability at the National Diet Library | en |
| dc.type | Article | |
| ifla.Unit | Section:Information Technology Section | |
| ifla.Unit | Section::Big Data Special Interest Group | |
| ifla.Unit | Section::Knowledge Management Section | |
| ifla.oPubId | https://library.ifla.org/id/eprint/2537/ |
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