
Hongbo Wang
Articles
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Jan 7, 2025 |
nature.com | Hongbo Wang |Tingting Mou
This paper intends to solve the limitations of the existing methods to deal with the comments of tourist attractions. With the technical support of Artificial Intelligence (AI), an online comment method of tourist attractions based on text mining model and attention mechanism is proposed. In the process of text mining, the attention mechanism is used to calculate the contribution of each topic to text representation on the topic layer of Latent Dirichlet Allocation (LDA). The Bidirectional Recurrent Neural Network (BiGRU) can effectively capture the temporal relationship and semantic dependence in the text through its powerful sequence modeling ability, thus achieving a more accurate classification of emotional tendencies. In order to verify the performance of the proposed ATT-LDA- Bigelow model, online comments about tourist attractions are collected from Ctrip.com, and users’ emotional tendencies towards different scenic spots are analyzed. The results show that this model has the best emotion classification effect in online comments of scenic spots, with the accuracy and F1 value reaching 93.85% and 93.68% respectively, which is superior to other emotion classification models. The proposed method not only improves the accuracy of sentiment analysis, but also provides strong support for the optimization of tourism recommendation system and provides more comprehensive, objective and accurate tourism information for scenic spot managers and tourism enterprises. This achievement is expected to bring new enlightenment and breakthrough to the research and practice in related fields.
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Nov 26, 2024 |
mdpi.com | Lei Zhang |Hongbo Wang |Yang Gao |Weixiong Huang
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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Oct 13, 2024 |
arxiv.org | Hongbo Wang |Lei Lu
arXiv:2410.09797 (cs) View PDF Comments: Subjects: Computer Vision and Pattern Recognition (cs.CV) Cite as: arXiv:2410.09797 [cs.CV] (or arXiv:2410.09797v1 [cs.CV] for this version) https://doi.org/10.48550/arXiv.2410.09797 Submission history From: Lei Lu [ view email] [v1] Sun, 13 Oct 2024 10:56:09 UTC (460 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?)...
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Oct 9, 2024 |
cell.com | Hongbo Wang
Keywordsbioinspired soft fingermultimodal sensorproprioceptiontactile sensingstiffness detectionrobotic palpationpulse-takingIntroductionWe use our hands not only to grasp/manipulate objects but also to explore and “feel” the world and interact with others via touch. Human hands are capable of dexterous manipulations1 and can perform highly skilled tasks empowered by fine motor control using sensory feedback and learning.
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Oct 6, 2024 |
mdpi.com | Xiaoyu Yuan |Jiawei Wang |Guang Zhao |Hongbo Wang
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
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