Xiangjie Kong

Xiangjie Kong
Zhejiang University of Technology · School of Computer Science and Technology

PhD

About

183
Publications
89,981
Reads
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4,607
Citations
Introduction
Xiangjie Kong received the Ph. D. degree from Zhejiang University, Hangzhou, China in 2009. Currently, he is a Professor with College of Computer Science and Technology, Zhejiang University of Technology. Dr. Kong has published over 100scientific papers in international journals and conferences (with 70+ indexed by ISI SCIE). His research interests include big traffic data, social computing, and cyber?physical systems. He is a Senior Member of IEEE and CCF, Member of ACM.
Additional affiliations
December 2019 - present
Zhejiang University of Technology
Position
  • Professor
December 2014 - December 2019
Dalian University of Technology
Position
  • Professor (Associate)
December 2009 - December 2014
Dalian University of Technology
Position
  • Professor (Assistant)

Publications

Publications (183)
Article
User-generated content on various Internet platforms is growing explosively, and contains valuable information that helps decision-making. However, extracting this information accurately is still a challenge since there are massive amounts of data. Thereinto, sentiment analysis solves this problem by identifying people’s sentiments towards the opin...
Article
With the constant development of innovative technologies and the resulting growth of new services available on the market, applications that aim to control devices employing smartphones include more extensive selection menus increasingly. This condition can lead to non-intuitive use of the system. As a result, the user may reap an adverse experienc...
Article
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With the continuous development of smart cities, intelligent transportation systems (ITSs) have ushered in many breakthroughs and upgrades. As a solid foundation for an ITS, traffic flow prediction effectively helps the city to better manage intricate traffic flow. However, existing traffic flow prediction methods such as temporal graph convolution...
Article
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With the development of intelligent transportation systems, clustering methods are now being adopted for traffic pattern recognition to discover the time-varying laws in road networks; this had attracted significant attention from the industry and academia over the past decades. Existing methods mainly focus on the mobility pattern and spatiotempor...
Article
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The International Cricket Council (ICC) uses the Duckworth-Lewis-Stern (DLS) method for resource compensation in interrupted games, which is an upgraded version of the Duckworth-Lewis (D/L) method. In order to compensate resources, the D/L method uses a generic resource table for all teams without considering both teams’ past performance, venue of...
Preprint
Full-text available
This paper elaborates how to identify and evaluate causal factors to improve scientific impact. Currently, analyzing scientific impact can be beneficial to various academic activities including funding application, mentor recommendation, and discovering potential cooperators etc. It is universally acknowledged that high-impact scholars often have m...
Preprint
Full-text available
Traffic flow prediction is an integral part of an intelligent transportation system and thus fundamental for various traffic-related applications. Buses are an indispensable way of moving for urban residents with fixed routes and schedules, which leads to latent travel regularity. However, human mobility patterns, specifically the complex relations...
Preprint
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Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide variety of areas, attracting considerable attention. The core step of GCNs is the information-passing framework that considers all information from neighbors to the central vertex to be equally important. Such equal importance, however, is inadequate for scale-free n...
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With the rapid development of the Internet and the widespread usage of mobile terminals, data-driven user profiling has become possible. User profiles describe the user’s overall behavior characteristic from multiple perspectives (e.g. basic information, feature preference, social attribute), which can explore the potential relationships between co...
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Due to the incomplete coverage and failure of traffic data collectors during the collection, traffic data usually suffers from information missing. Achieving accurate imputation is critical to the operation of transportation networks. Existing approaches usually focus on the characteristic analysis of temporal variation and adjacent spatial represe...
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Accurate real-time COVID-19 confirmed case prediction and risk stage evaluation are of great significance for government decision-making. However, the complexity of the epidemic spread and the lack of data in countries where COVID-19 has recently emerged are still an important challenge for researchers. In this paper, we propose a multi-feature rep...
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As one of the most serious hazards in the world, traffic accidents have caused huge casualties and property losses. The detection of abnormal behaviors of drivers is of great importance for intelligence transportation systems. However, the training of most abnormal behavior detection artificial intelligence algorithms demands huge computation and m...
Article
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This paper presents a rolling optimization algorithm for minimizing total vehicle delay for real-time traffic signal control in urban road networks, where the vehicle delay minimization problem is formulated as a quadratically-constrained quadratic programming problem, which is NP-hard. The programming problem is relaxed and resolved using the roll...
Article
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Congestion recognition is necessary for vehicle routing, traffic control, and many other applications in intelligent transportation systems. Besides, traffic facilities in the three-dimensional road network, which contains the fundamental spatiotemporal features for congestion recognition, provides multi-source traffic information. To exploit these...
Chapter
In contrast with the condition that the trajectory dataset of floating cars (taxis) can be easily obtained from the Internet, it is hard to get the trajectory data of social vehicles (private vehicles) because of personal privacy and government policies. This paper absorbs the idea of game theory, considers the influence of individuals in the group...
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Vehicle-to-vehicle (V2V) interaction and collaboration can provide us with a large number of mobile traffic trajectories that can be used to analyze driving behavior. In this paper, we propose a spatio-temporal cost combination based framework for taxi driving fraud detection (STC). First, the point of interest (POI) where taxis interact and collab...
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Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the qu...
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Full-text available
The ACM A.M. Turing Award is commonly acknowledged as the highest distinction in the realm of computer science. Since 1960s, it has been awarded to computer scientists who made outstanding contributions. The significance of this award is far-reaching to the laureates as well as their research teams. However, unlike the Nobel Prize that has been ext...
Article
Traffic flow prediction is the foundation of many applications in smart cities, and the granular precision of traffic flow prediction has to be enhanced with refined applications. However, most of the existing researches cannot meet these requirements. In this paper, we propose a spatial-temporal attention based fusion network (ST-AFN), for lane-le...
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Urban expressways provide an effective solution to traffic congestion, and ramp signal optimization can ensure the efficiency of expressway traffic. The existing methods are mainly based on the static spatial distance between mainline and ramp to achieve multi-ramp coordinated signal optimization, which lacks the consideration of the dynamic traffi...
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License plate is an essential characteristic to identify vehicles for the traffic management, and thus license plate recognition is important for Internet of Vehicles. Since 5G has been widely covered, mobile devices are utilized to assist the traffic management, which is a significant part of Industry 4.0. However, there have always been privacy r...
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Intelligent vehicle applications, such as autonomous driving and collision avoidance, put forward a higher demand for precise positioning of vehicles. The current widely used global navigation satellite systems (GNSS) cannot meet the precision requirements of the submeter level. Due to the development of sensing techniques and vehicle-to-infrastruc...
Preprint
Full-text available
Matching plays a vital role in the rational allocation of resources in many areas, ranging from market operation to people's daily lives. In economics, the term matching theory is coined for pairing two agents in a specific market to reach a stable or optimal state. In computer science, all branches of matching problems have emerged, such as the qu...
Article
Full-text available
Universities play an important role in exploring new concepts and knowledge transfer. University research naturally forms heterogeneous graphs through all real-life academic communication activities. In recent years, there have been many large scholarly graph datasets containing web-scale nodes and edges. However, so far, for these graph data, char...
Article
Modern enterprises attach much attention to the selection of commercial locations. With the rapid development of urban data and machine learning, we can discover the patterns of human mobility with these data and technology to guide commercial district discovery. In this paper, we propose an unsupervised commercial district discovery framework via...
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Full-text available
During the outbreak of COVID-19, while bringing various serious threats to the world, it reminds us that we need take precautions to control the transmission of the virus. The rise of Internet of Medical Things (IoMT) has made related data collection and processing, including healthcare monitoring systems, more convenient on the one hand, and requi...
Article
Embedded systems are common in the Internet of Things domain: their integration in vehicles and mobile devices is being fostered in the Internet of vehicles (IoV). IoV has direct applications on intelligent transportation systems and smart cities. Besides basic requirements, such as ease of installation, cost‐effectiveness, scalability, and flexibi...
Article
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Collaborative filtering has been successful in the recommendation systems of various scenarios, but it is also hampered by issues such as cold start and data sparsity. To alleviate the above problems, recent studies have attempted to integrate review information into models to improve accuracy of rating prediction. While most of the existing models...
Article
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The trust information in social networks among users is an important factor for the improvement of recommendation performance. Many successful recommendation tasks are treated as the matrix factorization problems. In this paper, we propose a novel trust-aware approach based on the recent advanced deep learning technique to alleviate the initializat...
Article
Full-text available
The car-following model describes the microscopic behavior of the vehicle. However, the existing car-following models set the drivers’ reaction time to a fixed value without considering its dynamics. In order to improve the accuracy of car-following model, this paper proposes Deep Feature Learning-based Car-Following Model (DeepCF), a car-following...
Chapter
Full-text available
As a part of the smart city, urban traffic safety has always received strong attention. For urban traffic safety, previous work often relies on some additional features and machine learning models, mainly considering whether accidents can be accurately predicted, but these work cannot be well integrated with smart cities. In order to better apply t...
Article
Full-text available
Congestion recognition is the prerequisite for traffic control and management, vehicle routing, and many other applications in intelligent transportation systems. Different types of roads with traffic facilities provide multi-source heterogeneous field traffic data, which contain the fundamental information and distinct features for congestion reco...
Article
Full-text available
The ACM A.M. Turing Award is commonly acknowledged as the highest distinction in the realm of computer science. Since 1960s, it has been awarded to computer scientists who made outstanding contributions. The significance of this award is far-reaching to the laureates as well as their research teams. However, unlike the Nobel Prize that has been ext...
Article
Full-text available
Networks are a general language for describing complex systems of interacting entities. In the real world, a network always contains massive nodes, edges and additional complex information which leads to high complexity in computing and analyzing tasks. Network embedding aims at transforming one network into a low dimensional vector space which ben...
Article
With the development of communication and information technologies, smart tourism is gradually changing the tourism industry. Internet of Things (IoT) plays an important role in smart tourism. However, it is a challenge to apply IoT for smart tourism because of the need for dealing with a vast amount of data and low-latency communication. To this e...
Preprint
Full-text available
Advisor-advisee relationship is important in academic networks due to its universality and necessity. Despite the increasing desire to analyze the career of newcomers, however, the outcomes of different collaboration patterns between advisors and advisees remain unknown. The purpose of this paper is to find out the correlation between advisors' aca...
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The advisor-advisee relationship represents direct knowledge heritage, and such relationship may not be readily available from academic libraries and search engines. This work aims to discover advisor-advisee relationships hidden behind scientific collaboration networks. For this purpose, we propose a novel model based on Network Representation Lea...
Article
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As a new computing paradigm, edge computing emerges in various fields. Many tasks previously deployed on the cloud are distributed to various edge devices such as wearable sensors, which cooperate to complete the tasks. However, circumstantial factors at the edge device (e.g., functionality, transmission efficiency, resource limitation) become more...
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Scholarly article impact reflects the significance of academic output recognised by academic peers, and it often plays a crucial role in assessing the scientific achievements of researchers, teams, institutions and countries. It is also used for addressing various needs in the academic and scientific arena, such as recruitment decisions, promotions...
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Quantifying the impact of a scholarly paper is of great significance, yet the effect of geographical distance of cited papers has not been explored. In this paper, we examine 30,596 papers published in Physical Review C, and identify the relationship between citations and geographical distances between author affiliations. Subsequently, a relative...
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With prosperity of applications on smartphones, energy saving for smartphones has drawn increasing attention. In this paper we devise Phone2Cloud, a computation offloading-based system for energy saving on smartphones in the context of mobile cloud computing. Phone2Cloud offloads computation of an application running on smartphones to the cloud. Th...
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Mobile devices have become a popular tool for ubiquitous learning in recent years. Multiple mobile users can be connected via ad hoc networks for the purpose of learning. In this context, due to limited battery capacity, energy efficiency of mobile devices becomes a very important factor that remarkably affects the user experience of mobile learnin...
Preprint
Globally, recommendation services have become important due to the fact that they support e-commerce applications and different research communities. Recommender systems have a large number of applications in many fields including economic, education, and scientific research. Different empirical studies have shown that recommender systems are more...
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Full-text available
Science of science has become a popular topic that attracts great attentions from the research community. The development of data analytics technologies and the readily available scholarly data enable the exploration of data-driven prediction, which plays a pivotal role in finding the trend of scientific impact. In this paper, we analyse methods an...
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A random walk is known as a random process which describes a path including a succession of random steps in the mathematical space. It has increasingly been popular in various disciplines such as mathematics and computer science. Furthermore, in quantum mechanics, quantum walks can be regarded as quantum analogues of classical random walks. Classic...
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This paper addresses the issues of selfishness, limited network resources, and their adverse effects on real-time dissemination of Emergency Warning Messages (EWMs) in modern Autonomous Moving Platforms (AMPs) such as Vehicular Social Networks (VSNs). For this purpose, we propose a social intelligence based identification mechanism to differentiate...
Article
Full-text available
With the widely used Internet of Things, 5G, and smart city technologies, we are able to acquire a variety of vehicle trajectory data. These trajectory data are of great significance which can be used to extract relevant information in order to, for instance, calculate the optimal path from one position to another, detect abnormal behavior, monitor...
Article
Full-text available
This article elaborates how to identify and evaluate causal factors to improve scientific impact. Currently, analyzing scientific impact can be beneficial to various academic activities including funding application, mentor recommendation, discovering potential cooperators, and the like. It is universally acknowledged that high-impact scholars ofte...