Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy-Reference-Cited by-同舟云学术

Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy

Published:2024-05-13 Issue: Volume:33 Page:1497-1508
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Kang SeongKu¹^ORCID,Agarwal Shivam¹^ORCID,Jin Bowen¹^ORCID,Lee Dongha²^ORCID,Yu Hwanjo³^ORCID,Han Jiawei¹^ORCID

Affiliation:

1. University of Illinois at Urbana-Champaign, Urbana, IL, USA

2. Yonsei University, Seoul, Republic of Korea

3. Pohang University of Science and Technology, Pohang, Republic of Korea

Funder

US DARPA KAIROS Program

the Institute for Geospatial Understanding through an Integrative Discovery Environment (I-GUIDE)

National Science Foundation

Molecule Maker Lab Institute: An AI Research Institutes program

INCAS Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645512

Reference60 articles.

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5. Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel S. Weld. 2020. SPECTER: Document-level Representation Learning using Citationinformed Transformers. In ACL.