A Roadmap to Domain Knowledge Integration in Machine Learning
It addresses the problem of enhancing model performance for ML practitioners by reviewing existing methods, making it incremental.
The paper provides an overview of different forms of knowledge integration in machine learning to address performance issues caused by inadequate data and resources, but does not present specific results or numbers.
Many machine learning algorithms have been developed in recent years to enhance the performance of a model in different aspects of artificial intelligence. But the problem persists due to inadequate data and resources. Integrating knowledge in a machine learning model can help to overcome these obstacles up to a certain degree. Incorporating knowledge is a complex task though because of various forms of knowledge representation. In this paper, we will give a brief overview of these different forms of knowledge integration and their performance in certain machine learning tasks.