A5073316564- Innovation, Sustainability, Human-Machine Systems
- Open Source Software Innovations
- Big Data and Business Intelligence
- Engineering Education and Technology
- Software Engineering Research
- Innovation Diffusion and Forecasting
- Multi-Agent Systems and Negotiation
- Intellectual Property and Patents
- Machine Learning in Materials Science
- Advanced Text Analysis Techniques
- Mobile Crowdsensing and Crowdsourcing
- Topic Modeling
Management Center Innsbruck
2023-2024
Universität Innsbruck
2023-2024
Applying artificial intelligence (AI), especially natural language processing (NLP), to harness large amounts of information from patent databases, online communities, social media, or crowdsourcing platforms is becoming increasingly popular help organizations find promising solutions. In the era non-human innovation intermediaries, we should begin view NLP not only as a useful technology applied in different practices but also an intermediary orchestrating valuable information. Previous...
Processing large and heterogeneous numbers of ideas submitted to crowdsourcing contests is a regular challenge for idea evaluators. The aim this study investigate potential use case AI-based innovation management extend the knowledge using automated novelty detection in evaluation processes. language models can automatically allocate short texts according their semantic similarity an embedded space. We represent content crowdsourced with three contemporary text embeddings – Doc2Vec, SBERT,...
Current approaches for identifying valuable content among the multitude of solutions in crowdsourcing contests are resource‐intensive and constrained by human processing capacity. As idea convergence processes usually focus on filtering out single ideas, potential solution‐related knowledge heterogeneous ideas is not exploited a sustainable manner. Transformer‐based language models can process large sets descriptions into digestible structures, with unprecedented capabilities understanding...