Researcher Representations Based on Aggregating Embeddings of Publication Titles: A Case Study in a Japanese Academic Database

Hiroyoshi Nagao, Marie Katsurai

Abstract
Constructing researcher representations is crucial for search and recommendation in academic databases. While recent studies presented methods based on knowledge graph embeddings, obtaining a complete graph of academic entities might be sometimes challenging due to the lack of linked data.By contrast, the textual list of publications of each researcher, which represents their research interests and expertise, is usually easy to obtain.Therefore, this study focuses on creating researcher representations based on textual embeddings of their publication titles and assesses their practicality. We aggregate embeddings of each researcher’s multiple publications into a single vector and apply it to research field classification and similar researcher search tasks. We experimented with multiple language models and embedding aggregation methods to compare their performance.From the model perspective, we confirmed the effectiveness of using sentence embedding models and a simple averaging approach.
Anthology ID:
2024.sdp-1.26
Volume:
Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Tirthankar Ghosal, Amanpreet Singh, Anita Waard, Philipp Mayr, Aakanksha Naik, Orion Weller, Yoonjoo Lee, Shannon Shen, Yanxia Qin
Venues:
sdp | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
277–282
Language:
URL:
https://aclanthology.org/2024.sdp-1.26
DOI:
Bibkey:
Cite (ACL):
Hiroyoshi Nagao and Marie Katsurai. 2024. Researcher Representations Based on Aggregating Embeddings of Publication Titles: A Case Study in a Japanese Academic Database. In Proceedings of the Fourth Workshop on Scholarly Document Processing (SDP 2024), pages 277–282, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Researcher Representations Based on Aggregating Embeddings of Publication Titles: A Case Study in a Japanese Academic Database (Nagao & Katsurai, sdp-WS 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-5/2024.sdp-1.26.pdf
PDF Search