Yang, Su, Deravi, Farzin (2022) Re-engineered word embeddings for improved document-level sentiment analysis. Applied Sciences, 12 (18). Article Number 9287. ISSN 2076-3417. (doi:10.3390/app12189287) (KAR id:106885)
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Official URL: https://doi.org/10.3390/app12189287 |
Abstract
In this paper, a novel re-engineering mechanism for the generation of word embeddings is proposed for document-level sentiment analysis. Current approaches to sentiment analysis often integrate feature engineering with classification, without optimizing the feature vectors explicitly. Engineering feature vectors to match the data between the training set and query sample as proposed in this paper could be a promising way for boosting the classification performance in machine learning applications. The proposed mechanism is designed to re-engineer the feature components from a set of embedding vectors for greatly increased between-class separation, hence better leveraging the informative content of the documents. The proposed mechanism was evaluated using four public benchmarking datasets for both two-way and five-way semantic classifications. The resulting embeddings have demonstrated substantially improved performance for a range of sentiment analysis tasks. Tests using all the four datasets achieved by far the best classification results compared with the state-of-the-art.
Item Type: | Article |
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DOI/Identification number: | 10.3390/app12189287 |
Uncontrolled keywords: | sentiment analysis; semantic classification; feature re-engineering; NLP |
Subjects: | T Technology > T Technology (General) |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Funders: | University of Kent (https://ror.org/00xkeyj56) |
SWORD Depositor: | JISC Publications Router |
Depositing User: | JISC Publications Router |
Date Deposited: | 15 Aug 2024 11:16 UTC |
Last Modified: | 15 Aug 2024 23:18 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/106885 (The current URI for this page, for reference purposes) |
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