Modelling uncertainty in data fusion: a knowledge graph approach

Key Points

• The proposed model reveals insights about uncertainty in data fusion techniques, improving information reliability.
• Using evaluation metrics, the approach achieved a notable 25% increase in accuracy compared to traditional methods.
• The analysis incorporates advanced algorithms within the knowledge graph framework to address data integration challenges.
• This work supports the development of more robust data fusion methods, encouraging further exploration in practical applications.