HiveScan
Map innovative companies of a field, with an innovation index you can decompose.
From the thesisText mining and topic modelling for innovation analysis
Thesis of Connor MacLean, conducted with funding from EDF
- Problem addressed
- Experts must screen many young companies with scattered and noisy information.
- Scientific contribution
- Text mining, named-entity recognition and topic models over company and scientific data; every score stays traceable.
- Origin
- PhD thesis of Connor MacLean
- Research themes
- Tech scouting in energy
Related
Theses and projects1
People2
Research themes1
Publications5
- Prétraitement syntaxique pour enrichir le Bag of Words en Topic Modeling2025 · 20e Conférence en Recherche d’Information et Applications (CORIA) 32ème Conférence sur le Traitement Automatique des Langues Naturelles (TALN) 27ème Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL) Les 18e Rencontres Jeunes Chercheurs en RI (RJCRI)
- Large-scale transformer-based topic graphs identify thematic links between engineering and biology2025 · Scientific Reports
- A Novel Interdisciplinarity Model Towards Inter-domain Information Pairing2024 · 24th International TRIZ Future Conference (TFC)
- Assessing Fine-Tuned NER Models with Limited Data in French: Automating Detection of New Technologies, Technological Domains, and Startup Names in Renewable Energy2024 · Machine Learning and Knowledge Extraction
- SynCRF: Syntax-Based Conditional Random Field for TRIZ Parameter Minings2024 · 16th International Conference on Agents and Artificial Intelligence, ICAART 2024, 24-26 February, 2024