Search Results for author: Bernd Kliem

Found 5 papers, 1 papers with code

sustain.AI: a Recommender System to analyze Sustainability Reports

1 code implementation15 May 2023 Lars Hillebrand, Maren Pielka, David Leonhard, Tobias Deußer, Tim Dilmaghani, Bernd Kliem, Rüdiger Loitz, Milad Morad, Christian Temath, Thiago Bell, Robin Stenzel, Rafet Sifa

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.

Multi-Label Classification Recommendation Systems

Towards automating Numerical Consistency Checks in Financial Reports

no code implementations11 Nov 2022 Lars Hillebrand, Tobias Deußer, Tim Dilmaghani, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa

It combines a financial named entity and relation extraction module with a BERT-based filtering and text pair classification component to extract KPIs from unstructured sentences before linking them to synonymous occurrences in the balance sheet and profit & loss statement.

Relation Extraction Text Pair Classification

Zero-Shot Text Matching for Automated Auditing using Sentence Transformers

no code implementations28 Oct 2022 David Biesner, Maren Pielka, Rajkumar Ramamurthy, Tim Dilmaghani, Bernd Kliem, Rüdiger Loitz, Rafet Sifa

Natural language processing methods have several applications in automated auditing, including document or passage classification, information retrieval, and question answering.

Information Retrieval Question Answering +5

KPI-BERT: A Joint Named Entity Recognition and Relation Extraction Model for Financial Reports

no code implementations3 Aug 2022 Lars Hillebrand, Tobias Deußer, Tim Dilmaghani, Bernd Kliem, Rüdiger Loitz, Christian Bauckhage, Rafet Sifa

We present KPI-BERT, a system which employs novel methods of named entity recognition (NER) and relation extraction (RE) to extract and link key performance indicators (KPIs), e. g. "revenue" or "interest expenses", of companies from real-world German financial documents.

named-entity-recognition Named Entity Recognition +4

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