Abstract

Enormous amount of data in varied formats is generated daily through various sources. Knowledge Graphs has got the amazing capability to fetch the information and efficiently organize it so as to explore the linkages of the Entities. Hence, ever since the Knowledge Graphs (KG) were introduced by Google in 2012, its popularity has increased in almost all fields owing to its promising performance. Many existing techniques are being replaced by Knowledge Graphs, taking into consideration, its efficient ways to extract the required information by interlinking the nodes. Though the researchers are working on generating a generic KG, so that it can cater more applications, still there are many challenges which the researchers are facing in achieving it. This paper focuses on investigating the Knowledge Graph Embedding, and Reasoning Techniques. The benefits and challenges of various methods for dealing with Embedding and Reasoning is being investigated and presented in the paper. At the end, to summarize the study, the various scopes of advancements in Knowledge Graph are also presented in brief. This investigation will help the researchers in paving different paths of application and research in Knowledge Graph Embedding and Reasoning.

References

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