Title: | The opportunities and challenges of word embeddings for source code vectorisation |
Subject: | Computer science, Software engineering |
Level: | Advanced |
Description: |
Word embedding is a popular technique to vectorize natural language processing. Word2Vec is a popular vectorisation method developed by google in 2013. Since then, there are continuous effort in improving the word embedding techniques. The investigation in this thesis requires studying existing word embedding techniques, find out the challenges and opportunities for the vectorization of software code, and offer potential improvements. Supervisor(s): Abu Naser Masud Examiner: |
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Prerequisites: | Machine learning, software engineering, programming in popular platforms for the implementation of machine learning tools such as python/keras |
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