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Mingsheng Shang 0001
Ming-Sheng Shang 0001
Person information
- affiliation: Chinese Academy of Sciences, Chongqing Institute of Green and Intelligent Technology, Chongqing, China
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2020 – today
- 2024
- [j70]Dexiu Ma
, Mei Liu
Neural dynamics solver for time-dependent infinity-norm optimization based on ACP framework with robot application. Neurocomputing 567: 127032 (2024) - [j69]Haoran Gu, Yunni Xia, Hong Xie
Robust and efficient algorithms for conversational contextual bandit. Inf. Sci. 657: 119993 (2024) - [j68]Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang
Asynchronous SGD with stale gradient dynamic adjustment for deep learning training. Inf. Sci. 681: 121220 (2024) - [j67]Wei Cui, Xuerui Zhang, Mingsheng Shang:
Multi-modality frequency-aware cross attention network for fake news detection. J. Intell. Fuzzy Syst. 46(1): 433-455 (2024) - [j66]Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang:
Adaptive moving average Q-learning. Knowl. Inf. Syst. 66(12): 7389-7417 (2024) - [j65]Bo Peng, Kefan Zhang, Long Jin, Mingsheng Shang:
A Transfer-Learning-Like Neural Dynamics Algorithm for Arctic Sea Ice Extraction. Neural Process. Lett. 56(4): 221 (2024) - [j64]Mei Liu
Orientation Tracking Incorporated Multicriteria Control for Redundant Manipulators With Dynamic Neural Network. IEEE Trans. Ind. Electron. 71(4): 3801-3810 (2024) - [j63]Mei Liu
Dynamic Neural Network for Motion/Force Control of Manipulators With Polynomial Noises. IEEE Trans. Ind. Electron. 71(10): 12559-12569 (2024) - [j62]Jiawang Tan
Metaheuristic-Based RNN for Manipulability Optimization of Redundant Manipulators. IEEE Trans. Ind. Informatics 20(4): 6489-6498 (2024) - [j61]Mei Liu
Data-Driven Remote Center of Cyclic Motion (RC$^{2}$M) Control for Redundant Robots With Rod-Shaped End-Effector. IEEE Trans. Ind. Informatics 20(4): 6772-6780 (2024) - [j60]Long Jin
Physical-Informed Neural Network for MPC-Based Trajectory Tracking of Vehicles With Noise Considered. IEEE Trans. Intell. Veh. 9(3): 4493-4503 (2024) - [j59]Ying Liufu
ACP-Incorporated Perturbation-Resistant Neural Dynamics Controller for Autonomous Vehicles. IEEE Trans. Intell. Veh. 9(4): 4675-4686 (2024) - [j58]Hong Xie
Probabilistic Modeling of Assimilate-Contrast Effects in Online Rating Systems. IEEE Trans. Knowl. Data Eng. 36(2): 795-808 (2024) - [j57]Mei Liu, Xiufang Chen
A Pseudoinversion-Free Method for Weight Updating in Broad Learning System. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2378-2389 (2024) - [j56]Xiaoyu Shi
Relieving Popularity Bias in Interactive Recommendation: A Diversity-Novelty-Aware Reinforcement Learning Approach. ACM Trans. Inf. Syst. 42(2): 52:1-52:30 (2024) - [j55]Xiaoyu Shi
Maximum Entropy Policy for Long-Term Fairness in Interactive Recommender Systems. IEEE Trans. Serv. Comput. 17(3): 1029-1043 (2024) - [j54]Liangming Chen
Enhancing Representation Power of Deep Neural Networks With Negligible Parameter Growth for Industrial Applications. IEEE Trans. Syst. Man Cybern. Syst. 54(11): 6837-6848 (2024) - [c51]Chongjun Xia, Xiaoyu Shi, Hong Xie, Quanliang Liu, Mingsheng Shang:
Hierarchical Reinforcement Learning for Long-term Fairness in Interactive Recommendation. ICWS 2024: 300-309 - [c50]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. ECML/PKDD (6) 2024: 145-162 - [i17]Yutong Chen, Hongzuo Xu, Guansong Pang, Hezhe Qiao, Yuan Zhou, Mingsheng Shang:
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection. CoRR abs/2406.19770 (2024) - 2023
- [j53]Xiaoyu Xu
Graph neural networks via contrast between separation and aggregation for self and neighborhood. Expert Syst. Appl. 224: 119994 (2023) - [j52]Bo Peng, Xuerui Zhang, Mingsheng Shang:
A Novel Competition-Based Coordination Model with Dynamic Feedback for Multi-Robot Systems. IEEE CAA J. Autom. Sinica 10(10): 2029-2031 (2023) - [j51]Mei Liu, Huanmei Wu, Mingsheng Shang:
A noise-suppressing discrete-time neural dynamics model for solving time-dependent multi-linear M-tensor equation. Neurocomputing 520: 240-249 (2023) - [j50]Wei Cui, Mingsheng Shang:
KAGN:knowledge-powered attention and graph convolutional networks for social media rumor detection. J. Big Data 10(1): 45 (2023) - [j49]Ye Yuan, Xin Luo
A Kalman-Filter-Incorporated Latent Factor Analysis Model for Temporally Dynamic Sparse Data. IEEE Trans. Cybern. 53(9): 5788-5801 (2023) - [j48]Mei Liu
Activated Gradients for Deep Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 34(4): 2156-2168 (2023) - [j47]Mei Liu, Li He, Mingsheng Shang
Dynamic Neural Network for Bicriteria Weighted Control of Robot Manipulators. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4570-4583 (2023) - [j46]Di Wu
Hyperparameter Learning for Deep Learning-Based Recommender Systems. IEEE Trans. Serv. Comput. 16(4): 2699-2712 (2023) - [j45]Mei Liu
Neural Solution to Dynamic Overdetermined System With Applications to Data Fitting and Parameters Estimation. IEEE Trans. Syst. Man Cybern. Syst. 53(12): 7330-7341 (2023) - [c49]Kexiang Zeng
Contrastive Learning based Item Representation with Asymmetric Augmentation for Sequential Recommendation. ADMIT 2023: 68-73 - [c48]Zhi Qi, Hong Xie, Mingsheng Shang:
A Predictive Coding Approach to Multivariate Time Series Anomaly Detection. DASFAA (1) 2023: 188-204 - [c47]Bingchao Wang, Xiaoyu Shi, Mingsheng Shang:
A Self-decoupled Interpretable Prediction Framework for Highly-Variable Cloud Workloads. DASFAA (1) 2023: 588-603 - [c46]Xiaoyu Shi, Quanliang Liu, Hong Xie, Mingsheng Shang:
Towards Long-term Fairness in Interactive Recommendation: A Maximum Entropy Reinforcement Learning Approach. ICWS 2023: 118-123 - [c45]Jinyu Mo, Hong Xie, Xiaoyu Shi, Mingsheng Shang:
CGCCMR: An Enhanced Multi-gate Model for Cross-Market Recommendation. IJCNN 2023: 1-8 - 2022
- [j44]Xiaoyu Xu, Di Wu
A structure-characteristic-aware network embedding model via differential evolution. Expert Syst. Appl. 204: 117611 (2022) - [j43]Mei Liu, Xiaoyan Zhang, Mingsheng Shang, Long Jin:
Gradient-Based Differential $k\text{WTA}$ Network With Application to Competitive Coordination of Multiple Robots. IEEE CAA J. Autom. Sinica 9(8): 1452-1463 (2022) - [j42]Mei Liu, Mingsheng Shang:
On RNN-Based $k$-WTA Models With Time-Dependent Inputs. IEEE CAA J. Autom. Sinica 9(11): 2034-2036 (2022) - [j41]Mei Liu, Jiazheng Zhang, Mingsheng Shang:
Real-time cooperative kinematic control for multiple robots in distributed scenarios with dynamic neural networks. Neurocomputing 491: 621-632 (2022) - [j40]Qing Li, Diwen Xiong, Mingsheng Shang:
Adjusted stochastic gradient descent for latent factor analysis. Inf. Sci. 588: 196-213 (2022) - [j39]Xiaoyu Xu, Guansong Pang
Joint hyperbolic and Euclidean geometry contrastive graph neural networks. Inf. Sci. 609: 799-815 (2022) - [j38]Qing Li, Guansong Pang
An efficient annealing-assisted differential evolution for multi-parameter adaptive latent factor analysis. J. Big Data 9(1): 95 (2022) - [j37]Lin Chen
MCFL: multi-label contrastive focal loss for deep imbalanced pedestrian attribute recognition. Neural Comput. Appl. 34(19): 16701-16715 (2022) - [j36]Long Jin
Distributed Competition of Multi-Robot Coordination Under Variable and Switching Topologies. IEEE Trans Autom. Sci. Eng. 19(4): 3575-3586 (2022) - [j35]Xiaoyu Shi
Large-Scale and Scalable Latent Factor Analysis via Distributed Alternative Stochastic Gradient Descent for Recommender Systems. IEEE Trans. Big Data 8(2): 420-431 (2022) - [j34]Ye Yuan
A Multilayered-and-Randomized Latent Factor Model for High-Dimensional and Sparse Matrices. IEEE Trans. Big Data 8(3): 784-794 (2022) - [j33]Yurong Zhong
Momentum-Incorporated Symmetric Non-Negative Latent Factor Models. IEEE Trans. Big Data 8(4): 1096-1106 (2022) - [j32]Mingsheng Shang
An α-β-Divergence-Generalized Recommender for Highly Accurate Predictions of Missing User Preferences. IEEE Trans. Cybern. 52(8): 8006-8018 (2022) - [j31]Mei Liu, Xiaoyan Zhang
Computational Neural Dynamics Model for Time-Variant Constrained Nonlinear Optimization Applied to Winner-Take-All Operation. IEEE Trans. Ind. Informatics 18(9): 5936-5948 (2022) - [j30]Di Wu
A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction. IEEE Trans. Knowl. Data Eng. 34(6): 2525-2538 (2022) - [j29]Di Wu
An L1-and-L2-Norm-Oriented Latent Factor Model for Recommender Systems. IEEE Trans. Neural Networks Learn. Syst. 33(10): 5775-5788 (2022) - [j28]Di Wu
A Posterior-Neighborhood-Regularized Latent Factor Model for Highly Accurate Web Service QoS Prediction. IEEE Trans. Serv. Comput. 15(2): 793-805 (2022) - [c44]Liangming Chen
Zero Stability Well Predicts Performance of Convolutional Neural Networks. AAAI 2022: 6268-6277 - [c43]Bo Sun, Di Wu, Mingsheng Shang, Yi He:
Toward Auto-Learning Hyperparameters for Deep Learning-Based Recommender Systems. DASFAA (2) 2022: 323-331 - [c42]Zihui Zhao, Xiaoyu Shi, Mingsheng Shang:
Performance and Cost-Aware Task Scheduling via Deep Reinforcement Learning in Cloud Environment. ICSOC 2022: 600-615 - [c41]Hao Liu, Hezhe Qiao, Xiaoyu Shi, Mingsheng Shang:
Aspect-aware Asymmetric Representation Learning Network for Review-based Recommendation. IJCNN 2022: 1-8 - [c40]Meijun Luo, Lin Chen, Yunni Xia, Mingsheng Shang:
Attention Auxiliary Spatial Fusion for Pedestrian Attribute Recognition. SMC 2022: 204-209 - [i16]Liangming Chen, Long Jin, Mingsheng Shang:
Zero Stability Well Predicts Performance of Convolutional Neural Networks. CoRR abs/2206.13100 (2022) - 2021
- [j27]Zhiting Wang, Guiyuan Shi, Mingsheng Shang, Yuxia Zhang:
The Stock Market Model with Delayed Information Impact from a Socioeconomic View. Entropy 23(7): 893 (2021) - [j26]Lin Chen, Saijun Gong, Xiaoyu Shi, Mingsheng Shang:
Dynamical Conventional Neural Network Channel Pruning by Genetic Wavelet Channel Search for Image Classification. Frontiers Comput. Neurosci. 15: 760554 (2021) - [j25]Bo Peng, Long Jin, Mingsheng Shang:
Multi-robot competitive tracking based on k-WTA neural network with one single neuron. Neurocomputing 460: 1-8 (2021) - [j24]Qing Li, Mingsheng Shang:
BALFA: A brain storm optimization-based adaptive latent factor analysis model. Inf. Sci. 578: 913-929 (2021) - [j23]Xin Luo
Algorithms of Unconstrained Non-Negative Latent Factor Analysis for Recommender Systems. IEEE Trans. Big Data 7(1): 227-240 (2021) - [j22]Xin Luo
Highly-Accurate Community Detection via Pointwise Mutual Information-Incorporated Symmetric Non-Negative Matrix Factorization. IEEE Trans. Netw. Sci. Eng. 8(1): 463-476 (2021) - [j21]Xin Luo
A Fast Non-Negative Latent Factor Model Based on Generalized Momentum Method. IEEE Trans. Syst. Man Cybern. Syst. 51(1): 610-620 (2021) - [j20]Xin Luo
An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data. IEEE Trans. Syst. Man Cybern. Syst. 51(6): 3522-3532 (2021) - [j19]Di Wu
A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(7): 4285-4296 (2021) - [j18]Xin Luo
Non-Negative Latent Factor Model Based on β-Divergence for Recommender Systems. IEEE Trans. Syst. Man Cybern. Syst. 51(8): 4612-4623 (2021) - [c39]Jianxiong Xu, Xiaoyu Shi, Hezhe Qiao, Mingsheng Shang, Xianbo He, Qingyu He:
UEIN: A User Evolving Interests Network for Click-Through Rate Prediction. BigDataSE 2021: 34-41 - [c38]Diwen Xiong, Mingsheng Shang:
RoboNet: a Neural Network Based Kinematic Parameter Identification Model. ICNSC 2021: 1-6 - [c37]Leming Zhou, Qing Li, Mingsheng Shang:
Chronic Disease Detection Via Non-negative Latent Feature Analysis. ICNSC 2021: 1-6 - [c36]Jiabao Zhong, Hezhe Qiao, Lin Chen, Mingsheng Shang, Qun Liu:
Improving Pedestrian Attribute Recognition with Multi-Scale Spatial Calibration. IJCNN 2021: 1-8 - [i15]Mei Liu, Liangming Chen, Xiaohao Du, Long Jin, Mingsheng Shang:
Activated Gradients for Deep Neural Networks. CoRR abs/2107.04228 (2021) - 2020
- [j17]Xin Luo
Non-Negativity Constrained Missing Data Estimation for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE Trans. Cybern. 50(5): 1844-1855 (2020) - [c35]Tao Wang, Xiaoyu Shi, Mingsheng Shang:
Diversity-Aware Top-N Recommendation: A Deep Reinforcement Learning Way. Big Data (CCF) 2020: 226-241 - [c34]Ye Yuan, Mingsheng Shang, Xin Luo
Temporal Web Service QoS Prediction via Kalman Filter-Incorporated Latent Factor Analysis. ECAI 2020: 561-568 - [c33]Qing Li, Mingsheng Shang:
A Compressed Sensing and Porous 9-7 Wavelet Transform-based Image Fusion Algorithm. SMC 2020: 4185-4191 - [c32]Chonghao Zhao, Xiaoyu Shi, Mingsheng Shang, Yiqiu Fang:
A Clustering-Based Collaborative Filtering Recommendation Algorithm via Deep Learning User Side Information. WISE (2) 2020: 331-342 - [c31]Ye Yuan, Xin Luo
A Generalized and Fast-converging Non-negative Latent Factor Model for Predicting User Preferences in Recommender Systems. WWW 2020: 498-507 - [i14]Khushnood Abbas
TempNodeEmb: Temporal Node Embedding considering temporal edge influence matrix. CoRR abs/2008.06940 (2020)
2010 – 2019
- 2019
- [j16]Qingxian Wang, Binbin Peng, Xiaoyu Shi, Tianqi Shang, Mingsheng Shang
DCCR: Deep Collaborative Conjunctive Recommender for Rating Prediction. IEEE Access 7: 60186-60198 (2019) - [j15]Mingsheng Shang, Xin Luo
Randomized latent factor model for high-dimensional and sparse matrices from industrial applications. IEEE CAA J. Autom. Sinica 6(1): 131-141 (2019) - [j14]Qingxian Wang, Minzhi Chen
A momentum-incorporated latent factorization of tensors model for temporal-aware QoS missing data prediction. Neurocomputing 367: 299-307 (2019) - [c30]Di Wu, Yi He
Online Feature Selection with Capricious Streaming Features: A General Framework. IEEE BigData 2019: 683-688 - [c29]Longyu Ran, Xiaoyu Shi, Mingsheng Shang:
SLAs-Aware Online Task Scheduling Based on Deep Reinforcement Learning Method in Cloud Environment. HPCC/SmartCity/DSS 2019: 1518-1525 - [c28]Yuanxin Lv, Xiaoyu Shi, Longyu Ran, Mingsheng Shang:
Random Forest-Based Ensemble Estimator for Concrete Compressive Strength Prediction via AdaBoost Method. ICNC-FSKD 2019: 557-565 - [c27]Mengzhen Luo, Xiaoyu Shi, Qianqian Ji, Mingsheng Shang, Xianbo He, Weiguo Tao:
A Deep Self-learning Classification Framework for Incomplete Medical Patents with Multi-label. ICNC-FSKD 2019: 566-573 - [c26]Qianqian Ji, Xiaoyu Shi, Mingsheng Shang:
A Deep Temporal Collaborative Filtering Recommendation Framework via Joint Learning from Long and Short-Term Effects. ISPA/BDCloud/SocialCom/SustainCom 2019: 959-966 - [c25]Di Wu
A Data-Aware Latent Factor Model for Web Service QoS Prediction. PAKDD (1) 2019: 384-399 - [c24]Jiajia Jiang, Yunni Xia, Mingsheng Shang:
A Fast Autoencoder-based Recommender. SMC 2019: 1732-1737 - 2018
- [j13]Qing-Xian Wang, Xin Luo
Incremental Slope-one recommenders. Neurocomputing 272: 606-618 (2018) - [j12]Di Wu
Self-training semi-supervised classification based on density peaks of data. Neurocomputing 275: 180-191 (2018) - [j11]Ye Yuan, Xin Luo
Effects of preprocessing and training biases in latent factor models for recommender systems. Neurocomputing 275: 2019-2030 (2018) - [j10]Wenhong Tian, Majun He, Wenxia Guo, Wenqiang Huang, Xiaoyu Shi, Mingsheng Shang, Adel Nadjaran Toosi
On minimizing total energy consumption in the scheduling of virtual machine reservations. J. Netw. Comput. Appl. 113: 64-74 (2018) - [j9]Di Wu
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications. IEEE Trans. Ind. Informatics 14(3): 909-920 (2018) - [j8]Xin Luo
An Inherently Nonnegative Latent Factor Model for High-Dimensional and Sparse Matrices from Industrial Applications. IEEE Trans. Ind. Informatics 14(5): 2011-2022 (2018) - [c23]Yelu Mao, Xiaoyu Shi, Mingsheng Shang, Ying Zhang:
TCR: Temporal-CNN for Reviews Based Recommendation System. ICDLT 2018: 71-75 - [c22]Binbin Peng, Lin Chen
Fully Convolutional Neural Networks for Tissue Histopathology Image Classification and Segmentation. ICIP 2018: 1403-1407 - [c21]Xiaoyu Shi, Mingsheng Shang, Wenhong Tian, Khushnood Abbas, Shuai Wang, Tianshu Wu:
Autonomic performance management of cloud server based on adaptive control method. ICNSC 2018: 1-6 - [c20]Di Wu
A self-training semi-supervised classification algorithm based on density peaks of data and differential evolution. ICNSC 2018: 1-6 - [c19]Zhigang Liu, Xin Luo
Accelerated Non-negative Latent Factor Analysis on High-Dimensional and Sparse Matrices via Generalized Momentum Method. SMC 2018: 3051-3056 - 2017
- [j7]Xiaoyu Shi, Xin Luo
Long-term performance of collaborative filtering based recommenders in temporally evolving systems. Neurocomputing 267: 635-643 (2017) - [j6]Jia Chen, Xin Luo
Performance of latent factor models with extended linear biases. Knowl. Based Syst. 123: 128-136 (2017) - [j5]Xin Luo
Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications. IEEE Trans. Ind. Informatics 13(6): 3098-3107 (2017) - [c18]Xiao-Yu Shi, Xin Luo
Empirical analysis of collaborative filtering-based recommenders in temporally evolving systems. ICNSC 2017: 406-412 - [c17]Ye Yuan, Xin Luo
Effect of linear biases in latent factor models on high-dimensional and sparse matrices from recommender systems. ICNSC 2017: 488-494 - [c16]Xin Luo
Symmetric Non-negative Latent Factor Models for Undirected Large Networks. IJCAI 2017: 2435-2442 - [c15]Yinyan Zhang
A dynamic neural controller for adaptive optimal control of permanent magnet DC motors. IJCNN 2017: 839-844 - [c14]Long Jin, Shuai Li, Xin Luo
Nonlinearly-activated noise-tolerant zeroing neural network for distributed motion planning of multiple robot arms. IJCNN 2017: 4165-4170 - [c13]Li-Yuan Xue, Rong-Qiang Zeng, Wei An, Qing-Xian Wang, Mingsheng Shang:
Experiments on Neighborhood Combination Strategies for Bi-objective Unconstrained Binary Quadratic Programming Problem. PAAP 2017: 444-453 - 2016
- [j4]Xin Luo
A Novel Approach to Extracting Non-Negative Latent Factors From Non-Negative Big Sparse Matrices. IEEE Access 4: 2649-2655 (2016) - [c12]Chao Huo, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
A Multi-parent Crossover Based Genetic Algorithm for Bi-Objective Unconstrained Binary Quadratic Programming Problem. BIC-TA (2) 2016: 10-19 - [c11]Khushnood Abbas
Discovering Items with Potential Popularity on Social Media. DASC/PiCom/DataCom/CyberSciTech 2016: 459-466 - [c10]Xin Luo
Efficient Extraction of Non-negative Latent Factors from High-Dimensional and Sparse Matrices in Industrial Applications. ICDM 2016: 311-319 - [c9]Li-Yuan Xue, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
Solving Bi-objective Unconstrained Binary Quadratic Programming Problem with Multi-objective Backbone Guided Search Algorithm. ICIC (2) 2016: 745-753 - [c8]Lei Song, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
Solving bi-objective unconstrained binary quadratic programming problem with multi-objective path relinking algorithm. ICNC-FSKD 2016: 289-293 - [c7]Chao Huo, Rong-Qiang Zeng, Yang Wang, Mingsheng Shang:
An Effective Genetic Algorithm with Uniform Crossover for Bi-objective Unconstrained Binary Quadratic Programming Problem. IDEAL 2016: 58-67 - [i13]Khushnood Abbas, Mingsheng Shang, Xin Luo:
Discovering items with potential popularity on social media. CoRR abs/1604.01131 (2016) - [i12]Khushnood Abbas, Mingsheng Shang, Shi-Min Cai, Xiaoyu Shi:
Identifying emerging influential Nodes in evolving networks: Exploiting strength of weak nodes. CoRR abs/1609.01357 (2016) - 2015
- [j3]Xiuqin Zhong, Hongguang Fu, Huadong Xia, Leina Yang, Mingsheng Shang:
A hybrid cognitive assessment based on ontology knowledge map and skills. Knowl. Based Syst. 73: 52-60 (2015) - [i11]Jian Gao, Yu-Wei Dong, Mingsheng Shang, Shi-Min Cai, Tao Zhou:
Group-based ranking method for online rating systems with spamming attacks. CoRR abs/1501.00677 (2015) - [i10]Lin-Feng Zhong, Jian-Guo Liu, Ming-Sheng Shang:
Iterative resource allocation based on propagation feature of node for identifying the influential nodes. CoRR abs/1505.03214 (2015) - [i9]Yao-Dong Zhao, Shi-Min Cai, Ming Tang, Mingsheng Shang:
A Fast Recommendation Algorithm for Social Tagging Systems : A Delicious Case. CoRR abs/1512.08325 (2015) - 2014
- [j2]Yuan Guan, Shimin Cai
Recommendation algorithm based on item quality and user rating preferences. Frontiers Comput. Sci. 8(2): 289-297 (2014) - [c6]Rong-Qiang Zeng, Ming-Sheng Shang:
Solving Three-Objective Flow Shop Problem with Fast Hypervolume-Based Local Search Algorithm. ICIC (2) 2014: 11-25 - [c5]Rong-Qiang Zeng, Ming-Sheng Shang:
Solving bi-objective flow shop problem with multi-objective path relinking algorithm. ICNC 2014: 343-348 - [i8]Wei Zeng, An Zeng, Hao Liu, Ming-Sheng Shang, Tao Zhou:
Uncovering the information core in recommender systems. CoRR abs/1402.6132 (2014) - 2013
- [i7]Qian-Ming Zhang, An Zeng, Ming-Sheng Shang:
Extracting the information backbone in online system. CoRR abs/1303.6369 (2013) - [i6]Wei Zeng, An Zeng, Ming-Sheng Shang, Yi-Cheng Zhang:
Membership in social networks and the application in information filtering. CoRR abs/1308.3059 (2013) - [i5]Wei Zeng, An Zeng, Ming-Sheng Shang, Yi-Cheng Zhang:
Information filtering in sparse online systems: recommendation via semi-local diffusion. CoRR abs/1308.3060 (2013) - 2012
- [c4]Sheng Huang, Mingsheng Shang, Shimin Cai:
A Hybrid Decision Approach to Detect Profile Injection Attacks in Collaborative Recommender Systems. ISMIS 2012: 377-386 - [i4]Kai Gong, Ming Tang, Hui Yang, Mingsheng Shang:
Variability of Contact Process in Complex Networks. CoRR abs/1204.0650 (2012) - 2010
- [j1]Duanbing Chen, Jingfa Liu, Yan Fu, Mingsheng Shang:
An efficient heuristic algorithm for arbitrary shaped rectilinear block packing problem. Comput. Oper. Res. 37(6): 1068-1074 (2010) - [c3]Yong Chen, Mingsheng Shang:
An Evaluation of Structure Based Similarity Indexes for Collaborative Filtering. WKDD 2010: 474-477 - [c2]Zhi-Dan Zhao, Mingsheng Shang:
User-Based Collaborative-Filtering Recommendation Algorithms on Hadoop. WKDD 2010: 478-481
2000 – 2009
- 2009
- [c1]Jie Liu, Mingsheng Shang, Duanbing Chen:
Personal Recommendation Based on Weighted Bipartite Networks. FSKD (5) 2009: 134-137 - [i3]Ming-Sheng Shang, Ci-Hang Jin, Tao Zhou, Yi-Cheng Zhang:
Collaborative filtering based on multi-channel diffusion. CoRR abs/0906.1148 (2009) - [i2]Ming-Sheng Shang, Zi-Ke Zhang, Tao Zhou, Yi-Cheng Zhang:
Collaborative filtering with diffusion-based similarity on tripartite graphs. CoRR abs/0906.5017 (2009) - [i1]Ming-Sheng Shang, Linyuan Lu, Yi-Cheng Zhang, Tao Zhou:
Empirical analysis of web-based user-object bipartite networks. CoRR abs/0909.4938 (2009)
Coauthor Index
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