Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157476
Title: Concept graph based semantic matching of articles
Authors: Lin, Yanwen
Keywords: Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Lin, Y. (2022). Concept graph based semantic matching of articles. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157476
Abstract: Natural Language Processing (NLP) is a luring area to explore. It allows machines to directly “understand” natural language, therefore operation based on text can be processed without further disposal, and human orders can be taken and implemented by machines without further programming, which enhance the user-friendliness for many industries. Past years have seen a rapid improvement of NLP. In current NLP technology, keyword detection is widely used for matching articles. However, this method overlooked the semantics of articles. On the other hand, the existing models targeting at semantic analysis take up large computational capacity. In this project, Concept Interaction Graph (CIG), a model generating semantic graphs from articles, was studied.
URI: https://hdl.handle.net/10356/157476
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

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