Book Chapter10.4018/978-1-7998-7701-1.CH010
Application of Machine Intelligence-Based Knowledge Graphs for Software Engineering
Raghavendra Rao Althar,Debabrata Samanta +1 more
- 01 Jan 2021
- pp 186-202
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TL;DR: This chapter focuses on knowledge graphs application in software engineering with a general exploration of artificial intelligence for software engineering and then funnels down to the area where knowledge graphs can be a good fit.
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Abstract: This chapter focuses on knowledge graphs application in software engineering. It starts with a general exploration of artificial intelligence for software engineering and then funnels down to the area where knowledge graphs can be a good fit. The focus is to put together work done in this area and call out key learning and future aspirations. The knowledge management system's architecture, specific application of the knowledge graph in software engineering like automation of test case creation and aspiring to build a continuous learning system are explored. Understanding the semantics of the knowledge, developing an intelligent development environment, defect prediction with network analysis, and clustering of the graph data are exciting explorations.
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Citations
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Performance Evaluation of Data-Centric Networks Based on Parallel and Distributed Architectures for Machine Intelligence Research
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References
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Fabian M. Suchanek,Gjergji Kasneci,Gerhard Weikum +2 more
- 08 May 2007
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Unsupervised word sense disambiguation rivaling supervised methods
David Yarowsky
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TL;DR: An unsupervised learning algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations.
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ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
TL;DR: ConceptNet as discussed by the authors is a knowledge graph that connects words and phrases of natural language with labeled edges to represent the general knowledge involved in understanding language, improving natural language applications by allowing the application to better understand the meanings behind the words people use.