Knowledge Discovery from Unstructured Data in Financial Services (KDF) Workshop
Authors: 
Sameena Shah, Xiaodan Zhu, Wenhu Chen, Manling Li, Armineh Nourbakhsh, Xiaomo Liu, Zhiqiang Ma, Charese Smiley, Yulong Pei, Akshat GuptaAuthors Info & Claims
Sameena Shah, Xiaodan Zhu, Wenhu Chen, Manling Li, Armineh Nourbakhsh, Xiaomo Liu, Zhiqiang Ma, Charese Smiley, Yulong Pei, Akshat GuptaAuthors Info & ClaimsPages 3464 - 3467
Abstract
Knowledge discovery from unstructured data, including business documents, web content, and news articles, has been a key AI challenge for the financial services industry. Comprehending these corpora and discovering knowledge from them, which could be textual, tabular, or graphic, are the cornerstone of supporting business decisions in the financial services domain, where information retrieval and content analysis techniques are of fundamental importance. We propose a workshop on knowledge discovery from unstructured data in financial services at SIGIR 2023 to highlight the current and emerging opportunities, invite original research, and prompt success sharing between researchers.
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Index Terms
- Knowledge Discovery from Unstructured Data in Financial Services (KDF) Workshop
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Information & Contributors
Information
Published In
July 2023
3567 pages
ISBN:9781450394086
DOI:10.1145/3539618
- General Chairs:
- Hsin-Hsi Chen,
- Wei-Jou (Edward) Duh,
- Hen-Hsen Huang,
- Program Chairs:
- Makoto P. Kato,
- Josiane Mothe,
- Barbara Poblete
Copyright © 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 18 July 2023
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SIGIR '23
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SIGIR '23: The 46th International ACM SIGIR Conference on Research and Development in Information Retrieval
July 23 - 27, 2023
Taipei, Taiwan
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Overall Acceptance Rate 792 of 3,983 submissions, 20%
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