Faculty Profiles - MATSUBARA, Shigeki

Papers - MATSUBARA, Shigeki

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Development of Generative AI Chatbot Using Q&A of Lectures for Enhancing Research Data Management in Universities

Wada Kazuhiro, Matsubara Shigeki

Proceedings of the Annual Conference of Academic Exchange for Information Environment and Strategy Vol. 2024 ( 0 ) page： 137 - 142 2024.12

Capabilities and Challenges of LLMs in Metadata Extraction from Scholarly Papers Reviewed

Watanabe Y., Ito K., Matsubara S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15493 page： 280 - 287 2024.12

Estimation of Relevance Between Datasets for Enhancing Accessibility of Research Artifacts Reviewed

Ito K., Matsubara S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15494 page： 97 - 103 2024.12

The Power of URLs in Scholarly Papers: Their Role as Metadata Sources for Data Repositories Reviewed

Wada K., Matsubara S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 15494 page： 85 - 92 2024.12

Enhancing accessibility of research data through metadata conversion and registration in institutional repositories: Practices in the field of Solar-Terrestrial Physics Open Access

SHINBORI Atsuki, NOSÉ Masahito, MIYOSHI Yoshizumi, HORI Tomoaki, OOHIRA Tsukasa, NAOE Chizuko, OKAMOTO Maiko, SAGARA Takeshi, AOKI Takaaki, MATSUBARA Shigeki, GAKIYA Rui, YAMADA Kazunari, IMAJO Shun, MINAMIYAMA Yasuyuki, ABE Shuji, TAKAHASHI Ichiro, TANAKA Yoshimasa, UENO Satoru, TANAKA Sachie, HAYASHI Hidekazu, HORI Yuko, ASHIKITA Takuya, OKAMURA Nanako, HIRANO Kaoru, SAITO Yasuo, SHIMIZU Toshiyuki

The Journal of Information Science and Technology Association Vol. 74 ( 11 ) page： 487 - 493 2024.11

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Information Science and Technology Association, Japan

The “Inter-university Upper atmosphere Global Observation NETwork (IUGONET)” project has developed a metadata database for ground-based observation data in Solar-Terrestrial Physics. In order to make this metadata database accessible to a wide range of research communities and the general public, we converted metadata in different metadata schema and registered them in academic institutional repositories. As a result, through regular harvesting between databases, the metadata has also been registered in the Institutional Repositories Database (IRDB), the Data Catalog Cross-Search System, and Google’s Dataset Search, significantly enhancing the visibility and accessibility of research data. Furthermore, effective metadata management was implemented in response to research metadata maintenance requests from policy-making bodies.

DOI： 10.18919/jkg.74.11_487

Open Access

CiNii Research

Utilization of Text Data for Response Timing Detection in Attentive Listening Reviewed

Yu Watanabe, Koichiro Ito, Shigeki Matsubara

Proceedings of Interspeech-2024 page： 3565 - 3569 2024.9

Estimating Metadata of Research Artifacts to Enhance their Findability Reviewed

Koichiro Ito, Shigeki Matsubara

Proceedings of 2024 IEEE 20th International Conference on e-Science (e-Science) page： 1 - 2 2024.9

On an Intermediate Task for Classifying URL Citations on Scholarly Papers Reviewed

Kazuhiro Wada, Masaya Tsunokake, Shigeki Matsubara

Proceeding of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING2024) 2024.5

Negation Scope Conversion: Towards a Unified Negation-Annotated Dataset Reviewed

Asahi Yoshida, Yoshihide Kato, Shigeki Matsubara

Proceeding of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING2024) 2024.5

Responsive Utterance Generation to Show Disagreement to Narrative in Attentive Listening Reviewed

Ito Koichiro, Murata Masaki, Ohno Tomohiro, Matsubara Shigeki

Journal of Natural Language Processing Vol. 31 ( 1 ) page： 212 - 249 2024.3

Authorship：Last author Language：Japanese Publishing type：Research paper (scientific journal) Publisher：The Association for Natural Language Processing

Conversational agents, such as communication robots, are expected to play a role in listening to narratives. To recognize these robots as the listeners, it is essential for them to have a function that indicates their attentive listening to a narrative. The basic response strategy in attentive listening involves generating responsive utterances that show acceptance. However, the narratives occasionally contain self-deprecation or modesty. In such cases, the listener must be able to produce a response that shows disagreement with the narrator's utterance, that is, a disagreement response. This study demonstrates the feasibility of generating appropriate disagreement responses. First, we define a method to tag the timing and expression of the disagreement response to narrative data in a non-real-time environment, and verify that the method enables to construct a corpus to which the disagreement response timing and response expression are comprehensively and stably assigned, respectively. Next, we implement detection and classification methods for disagreement response timing and expressions, respectively, based on a pre-trained transformer-based model and verify the feasibility of generating disagreement responses using the response corpus through experiments.

DOI： 10.5715/jnlp.31.212

CiNii Research

Re-Evaluating Syntax-Based Negation Scope Resolution

YOSHIDA Asahi, KATO Yoshihide, MATSUBARA Shigeki

IEICE Transactions on Information and Systems Vol. E107.D ( 1 ) page： 165 - 168 2024.1

Language：English Publishing type：Research paper (scientific journal) Publisher：The Institute of Electronics, Information and Communication Engineers

Negation scope resolution is the process of detecting the negated part of a sentence. Unlike the syntax-based approach employed in previous researches, state-of-the-art methods performed better without the explicit use of syntactic structure. This work revisits the syntax-based approach and re-evaluates the effectiveness of syntactic structure in negation scope resolution. We replace the parser utilized in the prior works with state-of-the-art parsers and modify the syntax-based heuristic rules. The experimental results demonstrate that the simple modifications enhance the performance of the prior syntax-based method to the same level as state-of-the-art end-to-end neural-based methods.

DOI： 10.1587/transinf.2023edl8050

Web of Science

Scopus

CiNii Research

Enhancing Findability and Searchability of Research Data: Metadata Conversion and Registration in Institutional Repositories Open Access

Nosé M., Shinbori A., Miyoshi Y., Hori T., Ohira T., Hashiba J., Naoe C., Gakiya R., Okamoto M., Sagara T., Aoki T., Matsubara S., Takahashi I., Hayashi H., Yamada K., Minamiyama Y., Tanaka Y., Abe S., Ueno S., Imajo S., Saito Y., Ashikita T., Hori Y., Shimizu T., Okamura N., Hirano K., Bargatze L.

Data Science Journal Vol. 23 2024

Citation-Worthy Detection of URL Citations in Scholarly Papers Open Access

Kazuhiro Wada, Masaya Tsunokake, Shigeki Matsubara

Proceedings of the 24th ACM/IEEE Joint Conference on Digital Libraries (JCDL-2024) ( 28 ) page： 1 - 5 2024

Negation Scope Conversion: Towards a Unified Negation-Annotated Dataset

Yoshida, A; Kato, Y; Matsubara, S

PROCEEDINGS OF THE 2024 JOINT INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS, LANGUAGE RESOURCES AND EVALUATION (LREC-COLING 2024) page： 12093 - 12099 2024

On an Intermediate Task for Classifying URL Citations on Scholarly Papers

Wada, K; Tsunokake, M; Matsubara, S

PROCEEDINGS OF THE 2024 JOINT INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS, LANGUAGE RESOURCES AND EVALUATION (LREC-COLING 2024) page： 12359 - 12369 2024

Negation Scope Conversion: Towards a Unified Negation-Annotated Dataset Reviewed

加藤芳秀, 松原茂樹

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation Vol. - page： 12093 - 12099 2024

Paper Recommendation Using Citation Contexts in Scholarly Documents Reviewed

Tomoki Ikoma, Shigeki Matsubara

Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation (PACLIC 37) 2023.12

Automatic Insertion of Commas and Linefeeds into Lecture Transcripts Based on Multi-task Learning Reviewed

Zhicheng Fang, Masaki Murata, Shigeki Matsubara:

Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation (PACLIC 37) 2023.12

Identifying Influential References in Scholarly Papers Using Citation Contexts Reviewed

Ikoma T., Matsubara S.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 14458 page： 152 - 161 2023.12

On the Use of Language Models for Function Identification of Citations in Scholarly Papers Reviewed

Tomoki Ikoma and Shigeki Matsubara

Proceedings of the 2nd Workshop on Information Extraction from Scientific Publications (WIESP 2023) 2023.11

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Papers - MATSUBARA, Shigeki