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Journal Articles

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2024
[j9]
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Xinyue Zhang, Zhaoxia Wang, Guitao Cao, Seng-Beng Ho:
Joint Weakly Supervised Image Emotion Analysis Based on Interclass Discrimination and Intraclass Correlation. IEEE Intell. Syst. 39(5): 82-89 (2024)
2023
[j8]
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Jingfeng Cui, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
Survey on sentiment analysis: evolution of research methods and topics. Artif. Intell. Rev. 56(8): 8469-8510 (2023)
[j7]
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Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria:
Learning-Based Stock Trending Prediction by Incorporating Technical Indicators and Social Media Sentiment. Cogn. Comput. 15(3): 1092-1102 (2023)
[j6]
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Erik Cambria, Rui Mao, Melvin Chen, Zhaoxia Wang, Seng-Beng Ho:
Seven Pillars for the Future of Artificial Intelligence. IEEE Intell. Syst. 38(6): 62-69 (2023)
[j5]
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Zhaoxia Wang, Zhenda Hu, Seng-Beng Ho, Erik Cambria, Ah-Hwee Tan:
MiMuSA - mimicking human language understanding for fine-grained multi-class sentiment analysis. Neural Comput. Appl. 35(21): 15907-15921 (2023)
2020
[j4]
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Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
Multi-Level Fine-Scaled Sentiment Sensing with Ambivalence Handling. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 28(4): 683-697 (2020)
[j3]
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Zhaoxia Wang, Seng-Beng Ho, Erik Cambria:
A review of emotion sensing: categorization models and algorithms. Multim. Tools Appl. 79(47): 35553-35582 (2020)
2016
[j2]
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Seng-Beng Ho:
A Principled Framework for General Adaptive Social Robotics. Int. J. Artif. Life Res. 6(2): 1-22 (2016)
1986
[j1]
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Seng-Beng Ho, Charles R. Dyer:
Shape Smoothing Using Medial Axis Properties. IEEE Trans. Pattern Anal. Mach. Intell. 8(4): 512-520 (1986)

Conference and Workshop Papers

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2024
[c28]
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Nicole Anne Teo Huiying, Zhaoxia Wang, Ezekiel En Zhe Ghe, Yee Sen Tan, Kevan Oktavio, Alexander Vincent Lewi, Allyne Zhang, Seng-Beng Ho:
DLVS4Audio2Sheet: Deep Learning-Based Vocal Separation for Audio into Music Sheet Conversion. PAKDD (Workshops) 2024: 95-107
2023
[c27]
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  - conf/bics/HoWQC23
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Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria:
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication. BICS 2023: 14-30
[c26]
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Autumn Teo, Zhaoxia Wang, Haibo Pen, Budhitama Subagdja, Seng-Beng Ho, Boon-Kiat Quek:
Knowledge Graph enhanced Aspect-Based Sentiment Analysis Incorporating External Knowledge. ICDM (Workshops) 2023: 791-798
[c25]
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Seng-Beng Ho:
Why is that a Good or Not a Good Frying Pan? - Knowledge Representation for Functions of Objects and Tools for Design Understanding, Improvement, and Generation. SSCI 2023: 121-128
2021
[c24]
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Zhenda Hu, Zhaoxia Wang, Seng-Beng Ho, Ah-Hwee Tan:
Stock Market Trend Forecasting Based on Multiple Textual Features: A Deep Learning Method. ICTAI 2021: 1002-1007
[c23]
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Xiwen Yang, Seng-Beng Ho:
Simultaneous Causal Noise Removal for Causal Rule Discovery and Learning. SSCI 2021: 1-7
2020
[c22]
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  - conf/ssci/HoEZ20
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Seng-Beng Ho, Mark Edmonds, Song-Chun Zhu:
Actional-Perceptual Causality: Concepts and Inductive Learning for AI and Robotics. SSCI 2020: 442-448
[c21]
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Seng-Beng Ho, Xiwen Yang, Therese Quieta:
Achieving Human Expert Level Time Performance for Atari Games - A Causal Learning Approach. SSCI 2020: 449-456
2019
[c20]
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Seng-Beng Ho, Xiwen Yang, Therese Quieta, Gangeshwar Krishnamurthy, Fiona Liausvia:
On Human-like Performance Artificial Intelligence: A Demonstration Using an Atari Game. CVPR Workshops 2019: 9-12
[c19]
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Seng-Beng Ho, Xiwen Yang, Therese Quieta, Gangeshwar Krishnamurthy, Fiona Liausvia:
On Human-Like Performance Artificial Intelligence - A Demonstration Using an Atari Game. ICAIS (2) 2019: 25-37
[c18]
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Seng-Beng Ho, Zhaoxia Wang:
On True Language Understanding. ICAIS (2) 2019: 87-99
[c17]
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Seng-Beng Ho, Zhaoxia Wang:
Language and Robotics: Complex Sentence Understanding. ICIRA (6) 2019: 641-654
2018
[c16]
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Zhaoxia Wang, Seng-Beng Ho, Zhiping Lin:
Stock Market Prediction Analysis by Incorporating Social and News Opinion and Sentiment. ICDM Workshops 2018: 1375-1380
[c15]
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Xiwen Yang, Seng-Beng Ho:
Learning Correlations and Causalities Through an Inductive Bootstrapping Process. SSCI 2018: 2270-2277
2017
[c14]
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Seng-Beng Ho:
Causal Learning versus Reinforcement Learning for Knowledge Learning and Problem Solving. AAAI Workshops 2017
[c13]
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Seng-Beng Ho, Fiona Liausvia:
On Inductive Learning of Causal Knowledge for Problem Solving. AAAI Workshops 2017
[c12]
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Seng-Beng Ho:
Principles of Noology: A Theory and Science of Intelligence for Natural and Artificial Intelligence. AAAI Spring Symposia 2017
[c11]
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Seng-Beng Ho:
The Role of Synchronic Causal Conditions in Visual Knowledge Learning. CVPR Workshops 2017: 9-16
2016
[c10]
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Seng-Beng Ho:
Cognitive Architecture for Adaptive Social Robotics. ICIRA (1) 2016: 549-562
[c9]
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Seng-Beng Ho, Fiona Liausvia:
A ground level causal learning algorithm. SSCI 2016: 1-6
2014
[c8]
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Seng-Beng Ho:
On Effective Causal Learning. AGI 2014: 43-52
[c7]
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Seng-Beng Ho, Fiona Liausvia:
A rapid learning and problem solving method: Application to the StarCraft game environment. CIHLI 2014: 110-117
2013
[c6]
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Seng-Beng Ho:
Operational Representation - A Unifying Representation for Activity Learning and Problem Solving. AAAI Fall Symposia 2013
[c5]
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Seng-Beng Ho, Fiona Liausvia:
Knowledge Representation, Learning, and Problem Solving for General Intelligence. AGI 2013: 60-69
[c4]
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  - conf/cihli/IyerH13
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Laxmi R. Iyer, Seng-Beng Ho:
Perception and prediction - A connectionist model. CIHLI 2013: 25-32
[c3]
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Seng-Beng Ho:
The Atoms of Cognition: Action Learning and Problem Solving. CogSci 2013
[c2]
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Seng-Beng Ho:
A grand challenge for computational intelligence a micro-environment benchmark for adaptive autonomous intelligent agents. IEEE IA 2013: 44-53
2012
[c1]
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Seng-Beng Ho:
The Atoms of Cognition: A Theory of Ground Epistemics. CogSci 2012

Informal and Other Publications

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2023
[i3]
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  - journals/corr/abs-2303-06152
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Seng-Beng Ho:
Why is That a Good or Not a Good Frying Pan? - Knowledge Representation for Functions of Objects and Tools for Design Understanding, Improvement, and Generation. CoRR abs/2303.06152 (2023)
2022
[i2]
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  - journals/corr/abs-2206-05273
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Seng-Beng Ho:
A General Framework for the Representation of Function and Affordance: A Cognitive, Causal, and Grounded Approach, and a Step Toward AGI. CoRR abs/2206.05273 (2022)
[i1]
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  - journals/corr/abs-2210-08994
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Seng-Beng Ho, Zhaoxia Wang, Boon-Kiat Quek, Erik Cambria:
Knowledge Representation for Conceptual, Motivational, and Affective Processes in Natural Language Communication. CoRR abs/2210.08994 (2022)

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