1. sustain.AI: a Recommender System to analyze Sustainability Reports
- Author
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Hillebrand, Lars, Pielka, Maren, Leonhard, David, Deußer, Tobias, Dilmaghani, Tim, Kliem, Bernd, Loitz, Rüdiger, Morad, Milad, Temath, Christian, Bell, Thiago, Stenzel, Robin, and Sifa, Rafet
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning ,H.3.3 - Abstract
We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies' sustainability reports. The tool leverages an end-to-end trainable architecture that couples a BERT-based encoding module with a multi-label classification head to match relevant text passages from sustainability reports to their respective law regulations from the Global Reporting Initiative (GRI) standards. We evaluate our model on two novel German sustainability reporting data sets and consistently achieve a significantly higher recommendation performance compared to multiple strong baselines. Furthermore, sustainAI is publicly available for everyone at https://sustain.ki.nrw/., Comment: Accepted at ICAIL 2023, 5 pages, 3 figure, 3 tables
- Published
- 2023
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