E3S Web Conf.
Volume 184, 20202nd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED 2020)
|Number of page(s)||4|
|Published online||19 August 2020|
CODE2VEC Based Cognitive Agent System to Retrieve Relevant Code Component from Repository
1 PG Scholar, Gokaraju Rangaraju Institute of Engineering and Technology, India
2 Asst. Professor, Department of CSE, Gokaraju Rangaraju Institute of Engineering and Technology, India
3 Professor, Department of CSE, MGIT-Hyd, India
Meghna Talari: email@example.com
The cognitive agent system helps to retrieve most relevant code component by introducing latest techniques. In this paper the authors used latest approach of code embedding which undergoes code2vec tokenization model by tokenizing and converting the code components present in the dataset into a numeric representation to create a input for neural network environment and also implemented cosine similarity matching technique to acquire the relevancy and perform retrieval of code component.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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