Harnessing Holistic Discourse Features And Triadic Interaction For Sentiment Quadruple Extraction In Dialogues,
2024
Singapore Management University
Harnessing Holistic Discourse Features And Triadic Interaction For Sentiment Quadruple Extraction In Dialogues, Bobo Li, Hao Fei, Lizi Liao, Et Al
Research Collection School Of Computing and Information Systems
Dialogue Aspect-based Sentiment Quadruple (DiaASQ) is a newly-emergent task aiming to extract the sentiment quadruple (i.e., targets, aspects, opinions, and sentiments) from conversations. While showing promising performance, the prior DiaASQ approach unfortunately falls prey to the key crux of DiaASQ, including insufficient modeling of discourse features, and lacking quadruple extraction, which hinders furthertask improvement. To this end, we introduce a novel framework that not only capitalizes on comprehensive discourse feature modeling, but also captures the intrinsic interaction for optimal quadruple extraction. On the one hand, drawing upon multiple discourse features, our approach constructs a token-level heterogeneous graph and enhances token …
Pam3s: Progressive Two-Stage Auction-Based Multi-Platform Multi-User Mutual Selection Scheme In Mcs,
2024
Singapore Management University
Pam3s: Progressive Two-Stage Auction-Based Multi-Platform Multi-User Mutual Selection Scheme In Mcs, Bin Luo, Xinghua Li, Yinbin Miao, Man Zhang, Ximeng Liu, Yanbing Ren, Xizhao Luo, Deng, Robert H.
Research Collection School Of Computing and Information Systems
Mobile crowdsensing (MCS) has been applied in various fields to realize data sharing, where multiple platforms and multiple Mobile Users () have appeared recently. However, aiming at mutual selection, the existing works ignore making ' utilities with the limited resources and platforms' utilities while achieving the desired sensing data quality maximum as far as possible. Thus, they cannot motivate both and platforms to participate. To address this problem, standing on both sides of and platforms with conflicting interests, we propose a Progressive two-stage Auction-based Multi-platform Multi-user Mutual Selection scheme (). Specifically, in, we treat mutual selection as a two-stage auction …
Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context,
2024
Singapore Management University
Market-Gan: Adding Control To Financial Market Data Generation With Semantic Context, Haochong Xia, Shuo Sun, Xinrun Wang, Bo An
Research Collection School Of Computing and Information Systems
Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making. Despite the development of financial market simulation methodologies, existing frameworks often struggle with adapting to specialized simulation context. We pinpoint the challenges as i) current financial datasets do not contain context labels; ii) current techniques are not designed to generate financial data with context as control, which demands greater precision compared to other modalities; iii) the inherent difficulties in generating context-aligned, high-fidelity data given the non-stationary, noisy nature of financial data. To address these challenges, our contributions are: i) we proposed the Contextual …
Recommendations With Minimum Exposure Guarantees: A Post-Processing Framework,
2024
Singapore Management University
Recommendations With Minimum Exposure Guarantees: A Post-Processing Framework, Ramon Lopes, Rodrigo Alves, Antoine Ledent, Rodrygo L. T. Santos, Marius Kloft
Research Collection School Of Computing and Information Systems
Relevance-based ranking is a popular ingredient in recommenders, but it frequently struggles to meet fairness criteria because social and cultural norms may favor some item groups over others. For instance, some items might receive lower ratings due to some sort of bias (e.g. gender bias). A fair ranking should balance the exposure of items from advantaged and disadvantaged groups. To this end, we propose a novel post-processing framework to produce fair, exposure-aware recommendations. Our approach is based on an integer linear programming model maximizing the expected utility while satisfying a minimum exposure constraint. The model has fewer variables than previous …
Machine Learning For Refining Knowledge Graphs: A Survey,
2024
Singapore Management University
Machine Learning For Refining Knowledge Graphs: A Survey, Budhitama Subagdja, D. Shanthoshigaa, Zhaoxia Wang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Knowledge graph (KG) refinement refers to the process of filling in missing information, removing redundancies, and resolving inconsistencies in knowledge graphs. With the growing popularity of KG in various domains, many techniques involving machine learning have been applied, but there is no survey dedicated to machine learning-based KG refinement yet. Based on a novel framework following the KG refinement process, this paper presents a survey of machine learning approaches to KG refinement according to the kind of operations in KG refinement, the training datasets, mode of learning, and process multiplicity. Furthermore, the survey aims to provide broad practical insights into …
Catnet: Cross-Modal Fusion For Audio-Visual Speech Recognition,
2024
Singapore Management University
Catnet: Cross-Modal Fusion For Audio-Visual Speech Recognition, Xingmei Wang, Jianchen Mi, Boquan Li, Yixu Zhao, Jiaxiang Meng
Research Collection School Of Computing and Information Systems
Automatic speech recognition (ASR) is a typical pattern recognition technology that converts human speeches into texts. With the aid of advanced deep learning models, the performance of speech recognition is significantly improved. Especially, the emerging Audio–Visual Speech Recognition (AVSR) methods achieve satisfactory performance by combining audio-modal and visual-modal information. However, various complex environments, especially noises, limit the effectiveness of existing methods. In response to the noisy problem, in this paper, we propose a novel cross-modal audio–visual speech recognition model, named CATNet. First, we devise a cross-modal bidirectional fusion model to analyze the close relationship between audio and visual modalities. Second, …
M3sa: Multimodal Sentiment Analysis Based On Multi-Scale Feature Extraction And Multi-Task Learning,
2024
Singapore Management University
M3sa: Multimodal Sentiment Analysis Based On Multi-Scale Feature Extraction And Multi-Task Learning, Changkai Lin, Hongju Cheng, Qiang Rao, Yang Yang
Research Collection School Of Computing and Information Systems
Sentiment analysis plays an indispensable part in human-computer interaction. Multimodal sentiment analysis can overcome the shortcomings of unimodal sentiment analysis by fusing multimodal data. However, how to extracte improved feature representations and how to execute effective modality fusion are two crucial problems in multimodal sentiment analysis. Traditional work uses simple sub-models for feature extraction, and they ignore features of different scales and fuse different modalities of data equally, making it easier to incorporate extraneous information and affect analysis accuracy. In this paper, we propose a Multimodal Sentiment Analysis model based on Multi-scale feature extraction and Multi-task learning (M 3 SA). …
Earnhft: Efficient Hierarchical Reinforcement Learning For High Frequency Trading,
2024
Singapore Management University
Earnhft: Efficient Hierarchical Reinforcement Learning For High Frequency Trading, Molei Qin, Shuo Sun, Wentao Zhang, Haochong Xia, Xinrun Wang, Bo An
Research Collection School Of Computing and Information Systems
High-frequency trading (HFT) is using computer algorithms to make trading decisions in short time scales (e.g., second-level), which is widely used in the Cryptocurrency (Crypto) market, (e.g., Bitcoin). Reinforcement learning (RL) in financial research has shown stellar performance on many quantitative trading tasks. However, most methods focus on low-frequency trading, e.g., day-level, which cannot be directly applied to HFT because of two challenges. First, RL for HFT involves dealing with extremely long trajectories (e.g., 2.4 million steps per month), which is hard to optimize and evaluate. Second, the dramatic price fluctuations and market trend changes of Crypto make existing algorithms …
Transition-Informed Reinforcement Learning For Large-Scale Stackelberg Mean-Field Games.,
2024
Singapore Management University
Transition-Informed Reinforcement Learning For Large-Scale Stackelberg Mean-Field Games., Pengdeng Li, Runsheng Yu, Xinrun Wang, Bo An
Research Collection School Of Computing and Information Systems
Many real-world scenarios including fleet management and Ad auctions can be modeled as Stackelberg mean-field games (SMFGs) where a leader aims to incentivize a large number of homogeneous self-interested followers to maximize her utility. Existing works focus on cases with a small number of heterogeneous followers, e.g., 5-10, and suffer from scalability issue when the number of followers increases. There are three major challenges in solving large-scale SMFGs: i) classical methods based on solving differential equations fail as they require exact dynamics parameters, ii) learning by interacting with environment is data-inefficient, and iii) complex interaction between the leader and followers …
Unsupervised Training Sequence Design: Efficient And Generalizable Agent Training,
2024
Singapore Management University
Unsupervised Training Sequence Design: Efficient And Generalizable Agent Training, Wenjun Li, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
To train generalizable Reinforcement Learning (RL) agents, researchers recently proposed the Unsupervised Environment Design (UED) framework, in which a teacher agent creates a very large number of training environments and a student agent trains on the experiences in these environments to be robust against unseen testing scenarios. For example, to train a student to master the “stepping over stumps” task, the teacher will create numerous training environments with varying stump heights and shapes. In this paper, we argue that UED neglects training efficiency and its need for very large number of environments (henceforth referred to as infinite horizon training) makes …
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On
Trajectory Data,
2024
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China
Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu
Journal of System Simulation
Abstract: A K neighbor-RElim (KNR) algorithm and a sequential KNbr-RElim (SKNR) algorithm are proposed to mine traffic congestion association rules and congestion propagation spatio-temporal association rules by vehicle trajectory data in a large-scale road network. The KNR algorithm extends the spatial topology constraint based on the RElim algorithm. The KNR can be used to mine the road links prone to congestion from the large-scale trajectory dataset in a large-scale road network and quantify the strength of association for congested road links. The SKNR algorithm expands the time dimension in the form of sliding window and can be applied for mining …
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory,
2024
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan
Journal of System Simulation
Abstract: As the combat systems develop towards clustering, coordination, unmanned, and intelligent direction, traditional combat system modeling methods are unable to reflect the complexity and intelligence of the combat systems. By drawing on symbiosis theory, this paper models and analyzes complex combat systems, and decomposes the complex combat system into various subsystems according to combat missions. The combat units, interaction modes, and combat environments in the subsystems are analyzed. The paper builds mathematical models to capture the collaborative interaction relationships between combat units, finally constructing a symbiotic model of complex combat systems. By the symbiosis principles and methods, quantitative analysis …
Action Recognition Model Of Directed Attention Based On Cosine Similarity,
2024
Command & Control Engineering College, Army Engineering University of PLA, Nanjing 210007, China
Action Recognition Model Of Directed Attention Based On Cosine Similarity, Chen Li, Ming He, Chen Dong, Wei Li
Journal of System Simulation
Abstract: Aiming at the lack of directionality of traditional dot product attention, this paper proposes a directed attention model (DAM) based on cosine similarity. To effectively represent the direction relationship between the spatial and temporal features of video frames, the paper defines the relationship function in the attention mechanism using the cosine similarity theory, which can remove the absolute value of the relationship between features. To reduce the computational burden of the attention mechanism, the operation is decomposed from two dimensions of time and space. The computational complexity is further optimized by combining linear attention operation. The experiment is divided …
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control
System,
2024
Unmanned System Research Institute, Northwestern Polytechnical University, Xi'an 710072, China
Overall Scheme Design And Integration Testing Of Hardware-In-The-Loop Simulation Of Guidance And Control System, Xiaofei Chang, Jiayue Jiao, Kang Chen, Wenxing Fu, Jie Yan
Journal of System Simulation
Abstract: Hardware-in-the-loop simulation system is a complex distributed simulation system, and its design and integration directly affect the system performance and construction goals. Based on years of experience, this paper first summarizes the design of the overall scheme and analyzes the performance requirements of real-time, compatibility, scalability, and security. Then, the paper describes the overall scheme of a typical hardware-in-the-loop simulation system, including the functional hierarchy, operation mechanism, and structural composition. Finally, it summarizes the contents and steps of the system integration testing, acceptance testing, and credibility evaluation method.
Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas,
2024
Department of Information and Communication, Academy of Army Armored Force, Beijing 100072, China
Combat Effectiveness Evaluation Method Of Homogeneous Cluster Equipment System Based On Rlomag+Eas, Guohui Zhang, Ang Gao, Ya'nan Zhang
Journal of System Simulation
Abstract: The equipment system is the reflection of the combat system from the perspective of equipment. The research on the combat effectiveness evaluation of the equipment system is of great practical significance for the optimization, construction, and development of the equipment system. Cluster equipment combat system confrontation is characterized by large-scale, highly dynamic and strong confrontation, and it is difficult to directly evaluate combat effectiveness with traditional methods. Aiming at the single task homogeneous cluster equipment system (such as UAV reconnaissance swarm and ground unmanned platform fire assault cluster), this paper regards the confrontation process of equipment system as the …
Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm,
2024
School of Electrical and Photoelectric Engineering, West Anhui University, Luan 237012, China
Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang
Journal of System Simulation
Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The …
Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine,
2024
Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing, Guangdong University of Technology, Guangzhou 510006, China
Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou
Journal of System Simulation
Abstract: To meet the needs of virtual multi-person collaborative disassembly and assembly system for different disassembly and assembly tasks, this paper proposes a data-driven method with configurable task sequence. Taking an aeroengine prototype as the research object, the paper studies the task elements of multi-person collaborative disassembly and assembly. It parameterizes and expresses the task based on JSON (JavaScript object notation) and drives the task sequence by JSON parametrical files, defining the interactive operation of each task step. The practice shows that this method is applied to the multi-person collaborative disassembly and assembly system, which makes the system configurable and …
Intelligent Airport Crowd Management Technology Based On Digital Twin,
2024
School of Computer Science and Engineering, South China University of Technology, Guangzhou 510000, China
Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai
Journal of System Simulation
Abstract: Given the need for intelligent emergency control and management of airport crowds, a smart control scheme for airport crowds based on digital twin is proposed. The scheme constructs an integrated crowd control system framework with four dimensions, including digital layer, modeling layer, functional layer, and application layer. It discusses and demonstrates the application effect of five important application modules. By using a data-driven crowd simulation model and intelligent optimization algorithm, the proposed scheme realizes the dynamic prediction and control optimization of the airport crowd status. The scheme can effectively improve the efficiency and intelligence level of airport crowd control …
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm,
2024
School of Automation, Nanjing University of Information Science & Technology, Nanjing 210044, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing 210044, China; Jiangsu Key Laboratory of Big Data Analysis Technology, Nanjing 210044, China;
Emergency Material Scheduling Based On Discrete Shuffled Frog Leaping Algorithm, Xiaoning Shen, Zhongpei Ge, Chengbin Yao, Liyan Song, Yufang Wang
Journal of System Simulation
Abstract: A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the …
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit,
2024
School of Automation Science & Engineering, Xi'an Jiaotong University, Xi'an 710049, China
Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu
Journal of System Simulation
Abstract: Due to factors such as simplified assumptions or equipment characteristic deviation, modeling errors are inevitable in the mechanism modeling of thermal power units. To deal with the problem, this paper proposes a novel model refinement method based on recursive subspace for the digital twin of thermal power units. Firstly, the digital twin models are built based on mechanism analysis and combined with small sample data of typical conditions, ensuring interpretability and generalization performance. Secondly, based on the recursive subspace identification method, the refinement model is built and updated online in real time to compensate for the modeling error, improving …
