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165 results on '"Xie, Kunqing"'

1. GraphAD: A Graph Neural Network for Entity-Wise Multivariate Time-Series Anomaly Detection

Author: Chen, Xu, Qiu, Qiu, Li, Changshan, and Xie, Kunqing
Subjects: Computer Science - Machine Learning, Computer Science - Information Retrieval
Abstract: In recent years, the emergence and development of third-party platforms have greatly facilitated the growth of the Online to Offline (O2O) business. However, the large amount of transaction data raises new challenges for retailers, especially anomaly detection in operating conditions. Thus, platforms begin to develop intelligent business assistants with embedded anomaly detection methods to reduce the management burden on retailers. Traditional time-series anomaly detection methods capture underlying patterns from the perspectives of time and attributes, ignoring the difference between retailers in this scenario. Besides, similar transaction patterns extracted by the platforms can also provide guidance to individual retailers and enrich their available information without privacy issues. In this paper, we pose an entity-wise multivariate time-series anomaly detection problem that considers the time-series of each unique entity. To address this challenge, we propose GraphAD, a novel multivariate time-series anomaly detection model based on the graph neural network. GraphAD decomposes the Key Performance Indicator (KPI) into stable and volatility components and extracts their patterns in terms of attributes, entities and temporal perspectives via graph neural networks. We also construct a real-world entity-wise multivariate time-series dataset from the business data of Ele.me. The experimental results on this dataset show that GraphAD significantly outperforms existing anomaly detection methods., Comment: SIGIR'22 Short Paper
Published: 2022
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2. Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting

Author: Fang, Zheng, Long, Qingqing, Song, Guojie, and Xie, Kunqing
Subjects: Computer Science - Machine Learning
Abstract: Spatial-temporal forecasting has attracted tremendous attention in a wide range of applications, and traffic flow prediction is a canonical and typical example. The complex and long-range spatial-temporal correlations of traffic flow bring it to a most intractable challenge. Existing works typically utilize shallow graph convolution networks (GNNs) and temporal extracting modules to model spatial and temporal dependencies respectively. However, the representation ability of such models is limited due to: (1) shallow GNNs are incapable to capture long-range spatial correlations, (2) only spatial connections are considered and a mass of semantic connections are ignored, which are of great importance for a comprehensive understanding of traffic networks. To this end, we propose Spatial-Temporal Graph Ordinary Differential Equation Networks (STGODE). Specifically, we capture spatial-temporal dynamics through a tensor-based ordinary differential equation (ODE), as a result, deeper networks can be constructed and spatial-temporal features are utilized synchronously. To understand the network more comprehensively, semantical adjacency matrix is considered in our model, and a well-design temporal dialated convolution structure is used to capture long term temporal dependencies. We evaluate our model on multiple real-world traffic datasets and superior performance is achieved over state-of-the-art baselines.
Published: 2021
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3. TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning

Author: Chen, Xu, Wang, Junshan, and Xie, Kunqing
Subjects: Computer Science - Machine Learning
Abstract: With the rapid growth of traffic sensors deployed, a massive amount of traffic flow data are collected, revealing the long-term evolution of traffic flows and the gradual expansion of traffic networks. How to accurately forecasting these traffic flow attracts the attention of researchers as it is of great significance for improving the efficiency of transportation systems. However, existing methods mainly focus on the spatial-temporal correlation of static networks, leaving the problem of efficiently learning models on networks with expansion and evolving patterns less studied. To tackle this problem, we propose a Streaming Traffic Flow Forecasting Framework, TrafficStream, based on Graph Neural Networks (GNNs) and Continual Learning (CL), achieving accurate predictions and high efficiency. Firstly, we design a traffic pattern fusion method, cleverly integrating the new patterns that emerged during the long-term period into the model. A JS-divergence-based algorithm is proposed to mine new traffic patterns. Secondly, we introduce CL to consolidate the knowledge learned previously and transfer them to the current model. Specifically, we adopt two strategies: historical data replay and parameter smoothing. We construct a streaming traffic dataset to verify the efficiency and effectiveness of our model. Extensive experiments demonstrate its excellent potential to extract traffic patterns with high efficiency on long-term streaming network scene. The source code is available at https://github.com/AprLie/TrafficStream., Comment: IJCAI-2021
Published: 2021

4. Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective

Author: Du, Lun, Chen, Xu, Gao, Fei, Fu, Qiang, Xie, Kunqing, Han, Shi, and Zhang, Dongmei
Subjects: Computer Science - Machine Learning
Abstract: Network Embedding aims to learn a function mapping the nodes to Euclidean space contribute to multiple learning analysis tasks on networks. However, the noisy information behind the real-world networks and the overfitting problem both negatively impact the quality of embedding vectors. To tackle these problems, researchers utilize Adversarial Training for Network Embedding (AdvTNE) and achieve state-of-the-art performance. Unlike the mainstream methods introducing perturbations on the network structure or the data feature, AdvTNE directly perturbs the model parameters, which provides a new chance to understand the mechanism behind. In this paper, we explain AdvTNE theoretically from an optimization perspective. Considering the Power-law property of networks and the optimization objective, we analyze the reason for its excellent results. According to the above analysis, we propose a new activation to enhance the performance of AdvTNE. We conduct extensive experiments on four real networks to validate the effectiveness of our method in node classification and link prediction. The results demonstrate that our method is superior to the state-of-the-art baseline methods., Comment: 11 pages, 0 figures, accepted by WSDM'22
Published: 2021
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5. TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting

Author: Chen, Xu, Zhang, Yuanxing, Du, Lun, Fang, Zheng, Ren, Yi, Bian, Kaigui, and Xie, Kunqing
Subjects: Computer Science - Machine Learning
Abstract: Traffic flow forecasting is of great significance for improving the efficiency of transportation systems and preventing emergencies. Due to the highly non-linearity and intricate evolutionary patterns of short-term and long-term traffic flow, existing methods often fail to take full advantage of spatial-temporal information, especially the various temporal patterns with different period shifting and the characteristics of road segments. Besides, the globality representing the absolute value of traffic status indicators and the locality representing the relative value have not been considered simultaneously. This paper proposes a neural network model that focuses on the globality and locality of traffic networks as well as the temporal patterns of traffic data. The cycle-based dilated deformable convolution block is designed to capture different time-varying trends on each node accurately. Our model can extract both global and local spatial information since we combine two graph convolutional network methods to learn the representations of nodes and edges. Experiments on two real-world datasets show that the model can scrutinize the spatial-temporal correlation of traffic data, and its performance is better than the compared state-of-the-art methods. Further analysis indicates that the locality and globality of the traffic networks are critical to traffic flow prediction and the proposed TSSRGCN model can adapt to the various temporal traffic patterns., Comment: Published as a conference paper at ICDM 2020
Published: 2020

6. Transfer Knowledge Between Sub-regions for Traffic Prediction Using Deep Learning Method

Author: Ren, Yi, Xie, Kunqing, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yin, Hujun, editor, Camacho, David, editor, Tino, Peter, editor, Tallón-Ballesteros, Antonio J., editor, Menezes, Ronaldo, editor, and Allmendinger, Richard, editor
Published: 2019
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7. Transfer Knowledge Between Sub-regions for Traffic Prediction Using Deep Learning Method

Author: Ren, Yi, primary and Xie, Kunqing, additional
Published: 2019
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8. Mining Dependencies Considering Time Lag in Spatio-Temporal Traffic Data

Author: Zhou, Xiabing, Hong, Haikun, Xing, Xingxing, Huang, Wenhao, Bian, Kaigui, Xie, Kunqing, 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, Dong, Xin Luna, editor, Yu, Xiaohui, editor, Li, Jian, editor, and Sun, Yizhou, editor
Published: 2015
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9. Metric-Based Multi-Task Grouping Neural Network for Traffic Flow Forecasting

Author: Hong, Haikun, Huang, Wenhao, Song, Guojie, Xie, Kunqing, 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, Zeng, Zhigang, editor, Li, Yangmin, editor, and King, Irwin, editor
Published: 2014
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10. A Spatial-temporal Topic Segmentation Model for Human Mobile Behavior

Author: Xing, Xingxing, Li, Man, Hu, Weisong, Huang, Wenhao, Song, Guojie, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Kobsa, Alfred, editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Weikum, Gerhard, editor, Li, Feifei, editor, Li, Guoliang, editor, Hwang, Seung-won, editor, Yao, Bin, editor, and Zhang, Zhenjie, editor
Published: 2014
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11. Deep Architecture for Traffic Flow Prediction

Author: Huang, Wenhao, Hong, Haikun, Li, Man, Hu, Weisong, Song, Guojie, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Motoda, Hiroshi, editor, Wu, Zhaohui, editor, Cao, Longbing, editor, Zaiane, Osmar, editor, Yao, Min, editor, and Wang, Wei, editor
Published: 2013
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12. Adaptive Weight Optimization for Classification of Imbalanced Data

Author: Huang, Wenhao, Song, Guojie, Li, Man, Hu, Weisong, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Sun, Changyin, editor, Fang, Fang, editor, Zhou, Zhi-Hua, editor, Yang, Wankou, editor, and Liu, Zhi-Yong, editor
Published: 2013
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13. An Adaption of Relief for Redundant Feature Elimination

Author: Wu, Tianshu, Xie, Kunqing, Nie, Chengkai, Song, Guojie, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wang, Jun, editor, Yen, Gary G., editor, and Polycarpou, Marios M., editor
Published: 2012
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14. Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models

Author: Xu, Dafeng, Song, Guojie, Gao, Peng, Cao, Rongzeng, Nie, Xinwei, Xie, Kunqing, 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, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Tang, Jie, editor, King, Irwin, editor, Chen, Ling, editor, and Wang, Jianyong, editor
Published: 2011
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15. Discrete Trajectory Prediction on Mobile Data

Author: Zhao, Nan, Huang, Wenhao, Song, Guojie, Xie, Kunqing, 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, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Du, Xiaoyong, editor, Fan, Wenfei, editor, Wang, Jianmin, editor, Peng, Zhiyong, editor, and Sharaf, Mohamed A., editor
Published: 2011
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16. GraphAD

Author: Chen, Xu, primary, Qiu, Qiu, additional, Li, Changshan, additional, and Xie, Kunqing, additional
Published: 2022
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17. Anchor Points Seeking of Large Urban Crowd Based on the Mobile Billing Data

Author: Huang, Wenhao, Dong, Zhengbin, Zhao, Nan, Tian, Hao, Song, Guojie, Chen, Guanhua, Jiang, Yun, Xie, Kunqing, 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, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cao, Longbing, editor, Feng, Yong, editor, and Zhong, Jiang, editor
Published: 2010
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18. Multi-Agent Cooperative Reinforcement Learning in 3D Virtual World

Author: Zhang, Ping, Ma, Xiujun, Pan, Zijian, Li, Xiong, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Tan, Ying, editor, Shi, Yuhui, editor, and Tan, Kay Chen, editor
Published: 2010
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19. Mining the Structure and Evolution of the Airport Network of China over the Past Twenty Years

Author: Dong, Zhengbin, Wu, Wenjie, Ma, Xiujun, Xie, Kunqing, Jin, Fengjun, 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, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Huang, Ronghuai, editor, Yang, Qiang, editor, Pei, Jian, editor, Gama, João, editor, Meng, Xiaofeng, editor, and Li, Xue, editor
Published: 2009
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20. Numerical Learning Method for Process Neural Network

Author: Wu, Tianshu, Xie, Kunqing, Song, Guojie, He, Xingui, 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, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Yu, Wen, editor, He, Haibo, editor, and Zhang, Nian, editor
Published: 2009
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21. Squeezing Long Sequence Data for Efficient Similarity Search

Author: Song, Guojie, Cui, Bin, Zheng, Baihua, Xie, Kunqing, Yang, Dongqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Zhang, Yanchun, editor, Yu, Ge, editor, Bertino, Elisa, editor, and Xu, Guandong, editor
Published: 2008
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22. An Optimized Process Neural Network Model

Author: Song, Guojie, Yang, Dongqing, Liu, Yunfeng, Cui, Bin, Wu, Ling, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kotagiri, Ramamohanarao, editor, Krishna, P. Radha, editor, Mohania, Mukesh, editor, and Nantajeewarawat, Ekawit, editor
Published: 2007
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23. CLAIM: An Efficient Method for Relaxed Frequent Closed Itemsets Mining over Stream Data

Author: Song, Guojie, Yang, Dongqing, Cui, Bin, Zheng, Baihua, Liu, Yunfeng, Xie, Kunqing, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kotagiri, Ramamohanarao, editor, Krishna, P. Radha, editor, Mohania, Mukesh, editor, and Nantajeewarawat, Ekawit, editor
Published: 2007
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24. A Freeway Exit Volume Prediction Method Based on Traffic Origin-Destination Stability Pattern

Author: ZHANG, Ping, ZHANG, Mingxin, SONG, Guojie, DONG, Xinpin, and XIE, Kunqing
Published: 2012
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25. Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective

Author: Du, Lun, primary, Chen, Xu, additional, Gao, Fei, additional, Fu, Qiang, additional, Xie, Kunqing, additional, Han, Shi, additional, and Zhang, Dongmei, additional
Published: 2022
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26. Mining Dependencies Considering Time Lag in Spatio-Temporal Traffic Data

Author: Zhou, Xiabing, primary, Hong, Haikun, additional, Xing, Xingxing, additional, Huang, Wenhao, additional, Bian, Kaigui, additional, and Xie, Kunqing, additional
Published: 2015
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27. Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting

Author: Fang, Zheng, primary, Long, Qingqing, additional, Song, Guojie, additional, and Xie, Kunqing, additional
Published: 2021
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28. TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning

Author: Chen, Xu, primary, Wang, Junshan, additional, and Xie, Kunqing, additional
Published: 2021
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29. Fast Hierarchy Preserving Graph Embedding via Subspace Constraints

Author: Chen, Xu, primary, Du, Lun, additional, Chen, Mengyuan, additional, Wang, Yun, additional, Long, Qingqing, additional, and Xie, Kunqing, additional
Published: 2021
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30. Metric-Based Multi-Task Grouping Neural Network for Traffic Flow Forecasting

Author: Hong, Haikun, primary, Huang, Wenhao, additional, Song, Guojie, additional, and Xie, Kunqing, additional
Published: 2014
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31. A Spatial-temporal Topic Segmentation Model for Human Mobile Behavior

Author: Xing, Xingxing, primary, Li, Man, additional, Hu, Weisong, additional, Huang, Wenhao, additional, Song, Guojie, additional, and Xie, Kunqing, additional
Published: 2014
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32. Accelerating sequence searching: dimensionality reduction method

Author: Song, Guojie, Cui, Bin, Zheng, Baihua, Xie, Kunqing, and Yang, Dongqing
Published: 2009
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33. Mining geographic episode association patterns of abnormal events in global earth science data

Author: Wu, TianShu, Song, GuoJie, Ma, XiuJun, Xie, KunQing, Gao, XiaoPing, and Jin, XingXing
Published: 2008
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34. Deep Architecture for Traffic Flow Prediction

Author: Huang, Wenhao, primary, Hong, Haikun, additional, Li, Man, additional, Hu, Weisong, additional, Song, Guojie, additional, and Xie, Kunqing, additional
Published: 2013
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35. Dynamic Geospatial Web Services Composition in Peer-to-Peer Networks

Author: Ma, Xiujun, Xie, Kunqing, Liu, Chen, Li, Chenyu, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Grumbach, Stéphane, editor, Sui, Liying, editor, and Vianu, Victor, editor
Published: 2005
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36. TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting

Author: Chen, Xu, primary, Zhang, Yuanxing, additional, Du, Lun, additional, Fang, Zheng, additional, Ren, Yi, additional, Bian, Kaigui, additional, and Xie, Kunqing, additional
Published: 2020
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37. An Adaption of Relief for Redundant Feature Elimination

Author: Wu, Tianshu, primary, Xie, Kunqing, additional, Nie, Chengkai, additional, and Song, Guojie, additional
Published: 2012
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38. Transportation Modes Identification from Mobile Phone Data Using Probabilistic Models

Author: Xu, Dafeng, primary, Song, Guojie, additional, Gao, Peng, additional, Cao, Rongzeng, additional, Nie, Xinwei, additional, and Xie, Kunqing, additional
Published: 2011
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39. Discrete Trajectory Prediction on Mobile Data

Author: Zhao, Nan, primary, Huang, Wenhao, additional, Song, Guojie, additional, and Xie, Kunqing, additional
Published: 2011
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40. Anchor Points Seeking of Large Urban Crowd Based on the Mobile Billing Data

Author: Huang, Wenhao, primary, Dong, Zhengbin, additional, Zhao, Nan, additional, Tian, Hao, additional, Song, Guojie, additional, Chen, Guanhua, additional, Jiang, Yun, additional, and Xie, Kunqing, additional
Published: 2010
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41. Numerical Learning Method for Process Neural Network

Author: Wu, Tianshu, primary, Xie, Kunqing, additional, Song, Guojie, additional, and He, Xingui, additional
Published: 2009
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42. Mining the Structure and Evolution of the Airport Network of China over the Past Twenty Years

Author: Dong, Zhengbin, primary, Wu, Wenjie, additional, Ma, Xiujun, additional, Xie, Kunqing, additional, and Jin, Fengjun, additional
Published: 2009
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43. Passenger Flow Prediction in Traffic System Based on Deep Neural Networks and Transfer Learning Method

Author: Ren, Yi, primary, Chen, Xu, additional, Wan, Sheng, additional, Xie, Kunqing, additional, and Bian, Kaigui, additional
Published: 2019
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44. Dynamic Geospatial Web Services Composition in Peer-to-Peer Networks

Author: Ma, Xiujun, primary, Xie, Kunqing, additional, Liu, Chen, additional, and Li, Chenyu, additional
Published: 2005
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45. Efficient discovery of multilevel spatial association rules using partitions

Author: Wang, Lizhen, Xie, Kunqing, Chen, Tao, and Ma, Xiuli
Published: 2005
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46. Using contour lines to generate digital elevation models for steep slope areas: a case study of the Loess Plateau in North China

Author: Xie, Kunqing, Wu, Yongqiu, Ma, Xiujun, Liu, Yu, Liu, Baoyuan, and Hessel, R
Published: 2003
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47. Crop characteristics and their temporal change on the Loess Plateau of China

Author: Wu, Yongqiu, Xie, Kunqing, Zhang, Qingchun, Zhang, Yan, Xie, Yun, Zhang, Guanghui, Zhang, Wenbo, and Ritsema, Coen J
Published: 2003
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48. Discovering spatio-temporal dependencies based on time-lag in intelligent transportation data

Author: Zhou, Xiabing, primary, Hong, Haikun, additional, Xing, Xingxing, additional, Bian, Kaigui, additional, Xie, Kunqing, additional, and Xu, Mingliang, additional
Published: 2017
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49. Using the traffic heterogeneity of Chinese toll highway networks for hierarchical clustering

Author: Fang, Shi, primary, Bian, Kaigui, additional, Hong, Haikun, additional, Xie, Kunqing, additional, and Fu, Yuwen, additional
Published: 2016
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50. Structure Feature Learning Method for Incomplete Data

Author: Zhou, Xiabing, primary, Xing, Xingxing, additional, Han, Lei, additional, Hong, Haikun, additional, Bian, Kaigui, additional, and Xie, Kunqing, additional
Published: 2016
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