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Autoren:
Winkel, Fabian; Geierhos, Michaela; Fink, Josef 
Dokumenttyp:
Konferenzbeitrag / Conference Paper 
Titel:
Evaluating Embedding Models for Retrieving ESG Information from Annual Business Reports 
Titel Konferenzpublikation:
ICIS 2024 Proceedings, 23, AI in Business and Society 
Konferenztitel:
International Conference on Information Systems (45., 2024, Bangkok) 
Konferenztitel:
International Conference on Information Systems (ICIS) 2024 Conference 
Tagungsort:
Bangkok, Thailand 
Jahr der Konferenz:
2024 
Datum Beginn der Konferenz:
15.12.2024 
Datum Ende der Konferenz:
18.12.2024 
Verlegende Institution:
Association for Information Systems (AIS) 
Jahr:
2024 
Seiten von - bis:
2621 
Sprache:
Englisch 
Stichwörter:
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 
Fakultät:
Fakultät für Informatik 
Institut:
INF 7 - Institut für Datensicherheit 
Professur:
Geierhos, Michaela 
(Forschungs)einrichtung UniBw M:
CODE 
Open Access ja oder nein?:
Ja / Yes