Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/70217
Title: Paraphrase detection of semantically equivalent text
Authors: Lim, Linus Ji Wei
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing
Issue Date: 2017
Abstract: 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.
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.
URI: http://hdl.handle.net/10356/70217
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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Amended FYP Report - Linus Lim Ji Wei.pdf
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Amended Final Year Report2.9 MBAdobe PDFView/Open

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