Paraphrase detection of semantically equivalent text

Paraphrase detection of semantically equivalent text

This project aims to explore the possibility of using neural networks/machine learning to train language models to be able to understand and read semantically equivalent text that contains technical knowledge/esoteric terms related to computing and computer science. Furthermore, an additional explor...

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Bibliographic Details
Main Author: Lim, Linus Ji Wei
Other Authors: Liu Yang
Format: Final Year Project
Language:English
Published: 2017
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Online Access:http://hdl.handle.net/10356/70217
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Institution: Nanyang Technological University
Language: English
Description
Summary:This project aims to explore the possibility of using neural networks/machine learning to train language models to be able to understand and read semantically equivalent text that contains technical knowledge/esoteric terms related to computing and computer science. Furthermore, an additional exploration step will be to determine the feasibility of using said language models to understand semantically equivalent code patches and to tell them apart.

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