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arXiv · 2005.04726

Knowledge Graph semantic enhancement of input data for improving AI

Shreyansh Bhatt·Amit Sheth·Valerie Shalin·Jinjin Zhao
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Abstract

Intelligent systems designed using machine learning algorithms require a large number of labeled data. Background knowledge provides complementary, real world factual information that can augment the limited labeled data to train a machine learning algorithm. The term Knowledge Graph (KG) is in vogue as for many practical applications, it is convenient and useful to organize this background knowledge in the form of a graph. Recent academic research and implemented industrial intelligent systems have shown promising performance for machine learning algorithms that combine training data with a knowledge graph. In this article, we discuss the use of relevant KGs to enhance input data for two applications that use machine learning -- recommendation and community detection. The KG improves both accuracy and explainability.

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Shreyansh Bhatt, Amit Sheth, Valerie Shalin, Jinjin Zhao. 2020-05-10. Knowledge Graph semantic enhancement of input data for improving AI. https://doi.org/10.1109/mic.2020.2979620

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