Opinion-based intelligent recommender system
With the recent development of Natural Language Processing (NLP), it is possible to extract sentiments from a text with given aspects. Collaborative Filtering techniques are used to recommend items to generate personalised recommendations based on similar users' preferences. Deep learning has g...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/147996 |
| _version_ | 1811691436136988672 |
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| author | Poh, Ying Xuan |
| author2 | Li Fang |
| author_facet | Li Fang Poh, Ying Xuan |
| author_sort | Poh, Ying Xuan |
| collection | NTU |
| description | With the recent development of Natural Language Processing (NLP), it is possible to extract sentiments from a text with given aspects. Collaborative Filtering techniques are used to recommend items to generate personalised recommendations based on similar users' preferences. Deep learning has grown popular in recent years for its immense accuracy over massive datasets. In this paper, we proposed to design an opinion-based intelligent recommender system utilising deep learning. This system incorporates aspect-based sentiment analysis to understand and quantify text, followed by performing collaborative filtering techniques to build a recommender system. For the aspect-based sentiment analysis task, it is executed by converting texts sentences into auxiliary sentences followed by classification training using Bidirectional Encoder Representations from Transformers(BERT) to quantify texts into ratings. For collaborative filtering, it is accomplished using a modified Neural Collaborative Filtering(NCF) that learns the user-item interactions by recognising the relationship between aspects and ratings to provide recommendations to different users. The results are evaluated towards the end and could be used for real-life applications. |
| first_indexed | 2024-10-01T06:19:51Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/147996 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:19:51Z |
| publishDate | 2021 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1479962021-12-03T05:33:05Z Opinion-based intelligent recommender system Poh, Ying Xuan Li Fang School of Computer Science and Engineering Wang Zhaoxia ASFLi@ntu.edu.sg, zhxwang720101@hotmail.com Engineering::Computer science and engineering With the recent development of Natural Language Processing (NLP), it is possible to extract sentiments from a text with given aspects. Collaborative Filtering techniques are used to recommend items to generate personalised recommendations based on similar users' preferences. Deep learning has grown popular in recent years for its immense accuracy over massive datasets. In this paper, we proposed to design an opinion-based intelligent recommender system utilising deep learning. This system incorporates aspect-based sentiment analysis to understand and quantify text, followed by performing collaborative filtering techniques to build a recommender system. For the aspect-based sentiment analysis task, it is executed by converting texts sentences into auxiliary sentences followed by classification training using Bidirectional Encoder Representations from Transformers(BERT) to quantify texts into ratings. For collaborative filtering, it is accomplished using a modified Neural Collaborative Filtering(NCF) that learns the user-item interactions by recognising the relationship between aspects and ratings to provide recommendations to different users. The results are evaluated towards the end and could be used for real-life applications. Bachelor of Engineering (Computer Science) 2021-04-22T02:43:11Z 2021-04-22T02:43:11Z 2021 Final Year Project (FYP) Poh, Y. X. (2021). Opinion-based intelligent recommender system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/147996 https://hdl.handle.net/10356/147996 en SCSE 20-0588 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering Poh, Ying Xuan Opinion-based intelligent recommender system |
| title | Opinion-based intelligent recommender system |
| title_full | Opinion-based intelligent recommender system |
| title_fullStr | Opinion-based intelligent recommender system |
| title_full_unstemmed | Opinion-based intelligent recommender system |
| title_short | Opinion-based intelligent recommender system |
| title_sort | opinion based intelligent recommender system |
| topic | Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/147996 |
| work_keys_str_mv | AT pohyingxuan opinionbasedintelligentrecommendersystem |