Conference Proceeding
Refine
Year of publication
- 2023 (30) (remove)
Document Type
- Conference Proceeding (30) (remove)
Keywords
- Natural language processing (3)
- Associated liquids (2)
- Future Skills (2)
- Information extraction (2)
- Interdisciplinarity (2)
- Power plants (2)
- Sustainability (2)
- Active learning (1)
- Agent-based simulation (1)
- Agile development (1)
- Android (1)
- Anomaly detection (1)
- Automation (1)
- Building Automation (1)
- Business Process Intelligence (1)
- CO2 (1)
- Carbon Dioxide (1)
- Clustering (1)
- Connected Automated Vehicle (1)
- Control (1)
- Datasets (1)
- Decision theory (1)
- Deep learning (1)
- Design Thinking (1)
- Digital transformation (1)
- Digital triage (1)
- Digital twin (1)
- District data model (1)
- District energy planning platform (1)
- Education (1)
- Electrocardiography (1)
- Electrochemistry (1)
- Elicit (1)
- Energy Disaggregation (1)
- Energy market design (1)
- Energy storage (1)
- Energy system planning (1)
- Future skills (1)
- Home Assistant (1)
- Home Automation Platform (1)
- Instagram store (1)
- Interculturality (1)
- Key competences (1)
- Machine Learning (1)
- Market modeling (1)
- Micromix (1)
- Minimum Risk Manoeuvre (1)
- Mpc (1)
- Natural Language Processing (1)
- Natural language understanding (1)
- Navigation (1)
- Neural networks (1)
- Open Source (1)
- Operational Design Domain (1)
- PLS (1)
- Path-following (1)
- Performance (1)
- Personality (1)
- Process Model Extraction (1)
- Process optimization (1)
- Profile extraction (1)
- Prototype (1)
- Quality control (1)
- Query learning (1)
- Relation classification (1)
- Renewable energy integration (1)
- Reproducible research (1)
- Sensors comparison (1)
- Smart Building (1)
- Social impact measurement (1)
- Society (1)
- Software (1)
- Stress testing (1)
- Sustainable engineering education (1)
- Teamwork (1)
- Text Mining (1)
- Text mining (1)
- Time-series synchronization (1)
- Transdisciplinarity (1)
- Transformative Competencies (1)
- Transiton of Control (1)
- Triage-app (1)
- Trustworthy artificial intelligence (1)
- V2X (1)
- Wearable electronic device (1)
- active learning (1)
- aircraft engine (1)
- combustion (1)
- emission index (1)
- hydrogen (1)
- lab work (1)
- nitric oxides (1)
- professional skills (1)
- purchase factor (1)
- shopping behavior (1)
- structural equation model (1)
Institute
- Fachbereich Elektrotechnik und Informationstechnik (15)
- ECSM European Center for Sustainable Mobility (7)
- Fachbereich Energietechnik (5)
- Fachbereich Luft- und Raumfahrttechnik (4)
- Fachbereich Medizintechnik und Technomathematik (4)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (4)
- Fachbereich Wirtschaftswissenschaften (3)
- Kommission für Forschung und Entwicklung (3)
- Solar-Institut Jülich (3)
- Nowum-Energy (2)
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate this challenge, Active Learning (AL) proposes promising data points to annotators they annotate next instead of a subsequent or random sample. This method is supposed to save annotation effort while maintaining model performance.
However, practitioners face many AL strategies for different tasks and need an empirical basis to choose between them. Surveys categorize AL strategies into taxonomies without performance indications. Presentations of novel AL strategies compare the performance to a small subset of strategies. Our contribution addresses the empirical basis by introducing a reproducible active learning evaluation (ALE) framework for the comparative evaluation of AL strategies in NLP.
The framework allows the implementation of AL strategies with low effort and a fair data-driven comparison through defining and tracking experiment parameters (e.g., initial dataset size, number of data points per query step, and the budget). ALE helps practitioners to make more informed decisions, and researchers can focus on developing new, effective AL strategies and deriving best practices for specific use cases. With best practices, practitioners can lower their annotation costs. We present a case study to illustrate how to use the framework.