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.
翻译:近年来开发了许多机器学习算法,以提高模型在人工智能不同方面的性能,但由于数据和资源不足,问题依然存在。将知识纳入机器学习模型可以在某种程度上帮助克服这些障碍。融入知识是一项复杂的任务,尽管由于各种形式的知识代表。在本文件中,我们将简要概述这些不同形式的知识整合及其在某些机器学习任务中的表现。