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Your search keyword '"Goh, Pey-Yun"' showing total 23 results
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23 results on '"Goh, Pey-Yun"'

3. Flower shop mobile chatbot.

Author

Tan, Andrew Xue-Yee, Chong, Lee-Ying, Chong, Siew-Chin, and Goh, Pey-Yun

Subjects
CHATBOTS, NATURAL language processing, DIGITAL technology, MACHINE learning, COMPUTER software, CUSTOMER satisfaction
Abstract

Chatbot is a computer program that mimics human conversation and performs streamlined communication with the user through text messages. The usage of chatbots in the commercial field has been increasing recently due to the enhancement of customer satisfaction and product sales. However, most chatbots depend on antiquated models that can only provide pre-programmed responses, which is unclear and erroneous. This paper aims to build an automated mobile chatbot for a flower shop to assist them in reducing costs, boosting the business's growth, and establishing connections with clients in an increasingly digital environment. The majority of robots have been around for about ten years and work by following rules. These kinds of chatbot answer to customers based on the rules for the conversation. The proposed chatbot is implemented by machine learning approaches and natural language processing algorithms to enhance the chatbot's adaptability and human-like qualities, the chatbot are learning from the unsolved question based on the admin given answer. Besides, the admin interface is created to ease the data management in the proposed chatbot. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Photo-based mobile progress tracking with cloud synchronization.

Author

Wong, Chee-Hong, Chong, Lee-Ying, Chong, Siew-Chin, and Goh, Pey-Yun

Subjects
CLOUD storage, PHOTOGRAPH albums, CELL phones, SYNCHRONIZATION, MOBILE apps, OBJECT tracking (Computer vision)
Abstract

Progress tracking enables people to monitor and gauge progress, identify areas of improvement, and take corrective actions if necessary. As mobile phones become a daily necessity, people prefer to store the snapped photo on their mobile phones to perform progress tracking. However, there are a few limitations to track progress using mobile phones, such as the haphazard placement of photos in smartphone albums makes it difficult for users to locate and compare previous photos, hindering effective progress monitoring. Besides, lack of a mechanism to add progress metrics to images, making it hard to track and compare the improvement over time. Lastly, the absence of a cloud-based storage solution for progress data results in potential data loss and the inability to synchronize progress across multiple devices. This paper aims to develop a mobile application to track the progress of all kinds of activities through the snapped photos. The proposed mobile app consists of a progress metric that tracks and monitors the progress accurately over time. Besides, the snapped photos are stored in the cloud, enabling users to synchronize their progress across multiple devices easily without the risk of data loss. The proposed progress tracker app presents a useful solution for individuals seeking to track and monitor their progress of various aspects of their lives with photo. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Identifying and Removing Outlier Features Using Neighborhood Rough Set

Author

Goh, Pey Yun, Tan, Shing Chiang, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Kim, Kuinam J., editor, and Kim, Hye-Young, editor

Published
2020
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9. A Revisit of Reducing Hidden Nodes in a Radial Basis Function Neural Network with Histogram

Author

Goh, Pey Yun, Tan, Shing Chiang, Cheah, Wooi Ping, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Cheng, Long, editor, Leung, Andrew Chi Sing, editor, and Ozawa, Seiichi, editor

Published
2018
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14. Anomaly Detection Using Correctness Matching Through a Neighborhood Rough Set

Author

Goh, Pey Yun, Tan, Shing Chiang, Cheah, Wooi Ping, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Hirose, Akira, editor, Ozawa, Seiichi, editor, Doya, Kenji, editor, Ikeda, Kazushi, editor, Lee, Minho, editor, and Liu, Derong, editor

Published
2016
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