Build knowledge graph from heterogeneous documents

Abstract

Knowledge graphs are applied in many fields such as search engines, semantic analysis, and question answering in recent years. However, there are many obstacles for building knowledge graphs as methodologies, data and tools. This paper introduces a novel methodology to build knowledge graph from heterogeneous documents. We use the methodologies of natural language processing and deep learning to build this graph. The knowledge graph can use in question answering systems and Information retrieval especially in computing domain.