  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.
