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Authors:
Winkel, Fabian; Geierhos, Michaela; Fink, Josef
Document type:
Konferenzbeitrag / Conference Paper
Title:
Evaluating Embedding Models for Retrieving ESG Information from Annual Business Reports
Title of conference publication:
ICIS 2024 Proceedings, 23, AI in Business and Society
Conference title:
International Conference on Information Systems (45., 2024, Bangkok)
Conference title:
International Conference on Information Systems (ICIS) 2024 Conference
Venue:
Bangkok, Thailand
Year of conference:
2024
Date of conference beginning:
15.12.2024
Date of conference ending:
18.12.2024
Publishing institution:
Association for Information Systems (AIS)
Year:
2024
Pages from - to:
2621
Language:
Englisch
Keywords:
ESG statements ; annual business reports ; retrieval systems ; language model selection
Abstract:
Development Goals (SDG) has become paramount. Companies embed their ESG achievements, plans, and commitments into their annual reports in a non-standardized textual format. We propose a retrieval system for increasing transparency and comparability in ESG reporting, enabling various stakeholders to compare sustainability statements across annual reports. We employed qualitative and quantitative evaluation methods to select the most suitable embedding model for the proposed ESG retrieval applicat...     »
Article ID:
2621
URL:
https://aisel.aisnet.org/icis2024/aiinbus/aiinbus/23
Department:
Fakultät für Informatik
Institute:
INF 7 - Institut für Datensicherheit
Chair:
Geierhos, Michaela
Research Hub UniBw M:
CODE
Open Access yes or no?:
Ja / Yes
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