近期论文
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（1）期刊论文
刘业政，钱洋，姜元春，J Shang，Using Favorite Data to Analyze Asymmetric Competition: Machine Learning Models, European Journal of Operational Research, doi.org/10.1016/j.ejor.2020.03.074, 2020
刘业政，Zhe Li，Chong Zhou，姜元春，孙见山，Meng Wang ; Xiangnan He，Generative Adversarial Active Learning for Unsupervised Outlier Detection， IEEE Transactions on Knowledge and Data Engineering，10.1109/TKDE.2019.2905606, 2020
钱洋，刘业政，姜元春，刘晓，Detecting topic-level influencers in large-scale scientific networks，World Wide Web 23 (2), 831-851，2020
刘业政，杜非，孙见山，姜元春，iLDA: An interactive latent Dirichlet allocation model to improve topic quality，Journal of Information Science 46 (1), 23-40，2020
钱洋，姜元春，杜亚楠，孙见山，刘业政，Segmenting market structure from multi-channel clickstream data: a novel generative model，Electronic Commerce Research, 1-25，2019
孙见山，应蓉蓉，姜元春，丁正平，何建民，Leveraging friend and group information to improve social recommender system，Electronic Commerce Research, 1-26，2019
姜元春，陶丹丹，刘业政，孙见山，Cloud service recommendation based on unstructured textual information，Future Generation Computer Systems 97, 387-396，2019
刘业政，杜非，孙见山，T Silva, 姜元春，朱婷婷，Identifying social roles using heterogeneous features in online social networks，Journal of the Association for Information Science and Technology 70 (7): 660-674, 2019
刘业政，朱婷婷，姜元春，刘晓，Service matchmaking for Internet of Things based on probabilistic topic model，Future Generation Computer Systems 94, 272-281，2019
刘业政，熊强，孙见山，姜元春，T Silva，凌海峰，Topic-based hierarchical Bayesian linear regression models for niche items recommendation，Journal of Information Science 45 (1), 92-104，2019
刘业政，田志强，孙见山，姜元春，Distributed representation learning via node2vec for implicit feedback recommendation，Neural Computing and Applications, 1-11，2019
姜元春，刘业政，Jennifer Shang，Pinar Yildirim，Qingfu Zhang，Optimizing Online Recurring Promotions for Dual-Channel Retailers: Segmented Markets with Multiple Objectives，European Journal of Operational Research 267 (2), 612-627, 2018
姜元春, 刘业政, Hai Wang, Jennifer Shang, 丁帅, Online pricing with bundling and coupon discounts, International Journal of Production Research 56 (5), 1773-1788, 2018
刘业政, 王佳佳, 姜元春, 孙见山, Jennifer Shang, Identifying Impact of Intrinsic Factors on Topic Preferences in Online Social Media: A Nonparametric Hierarchical Bayesian Approach,
Information Sciences 423, 219-234, 2018
王锦坤, 姜元春, 孙见山,刘业政, 刘晓, Group recommendation based on a bidirectional tensor factorization model,World Wide Web 21 (4), 961-984, 2018
孙见山, 姜元春, 程絮森, 刘业政, A hybrid approach for article recommendation in research social networks, Journal of Information Science 44 (5), 696-711, 2018
王锦坤, 张莎莎, 刘晓, 姜元春, A novel collective matrix factorization model for recommendation with fine‐grained social trust prediction, Concurrency and Computation: Practice and Experience 29 (19), e4233, 2017
刘业政，杨露，孙见山，姜元春，Collaborative Matrix Factorization Mechanism for Group Recommendation in big data-based library systems，Library Hi Tech，2017
李旭军, 刘业政,姜元春, Identifying Social Influence in Complex Networks: A Novel Conductance Eigenvector Centrality Model, Neurocomputing, Neurocomputing 210 (2016): 141-154 （通讯作者）
刘业政, 王佳佳, 姜元春, PT-LDA:A Latent Variable Model to Predict Personality Traits of Social Network Users, Neurocomputing, 210 (2016): 155-163（通讯作者）
姜元春, Jennifer Shang, 刘业政, Jerrold May, Redesigning promotion strategy for e-commerce competitiveness through pricing and recommendation, International Journal of Production Economics, 167: 257-270, 2015.
姜元春*, Jennifer Shang, 刘业政, Optimizing Shipping-Fee Schedules to Maximize E-tailer Profits, International Journal of Production Economics, 146(2): 634-645, 2013
姜元春, Jennifer Shang*, Chris F. Kemerer, 刘业政, Optimizing E-tailer Profits and Customer Savings: An Online Dynamic Bundle Pricing Model, Marketing Science, 30(4): 737-752, 2011
姜元春*, Jennifer Shang, 刘业政, Maximizing Customer Satisfaction through an Online Recommendation System: A Novel Associative Classification Model, Decision Support Systems, 48(3),pp. 470-479, 2010 .
姜元春*, 刘业政, Optimization of Online Promotion: A Profit-Maximizing Model Integrating Price Discount and Product Recommendation, International Journal of Information Technology and Decision Making, 11(5): 1-22, 2012
姜元春*, 刘业政, 刘晓, Integrating Classification Capability and Reliability in Associative Classification: A β-Stronger Model, Expert Systems With Applications, 37(5): 3953-3961, 2010
刘业政*, 姜元春, 杨善林, CSMC: A Combination Strategy for Multi-class Classification based on Multiple Association Rules, Knowledge-Based Systems, 21(8),pp. 786-793, 2008
陈思凤, 姜元春*, 刘业政, Cost Constrained Mediation Model for AHP Negotiated Decision Making, Journal of Multi-Criteria Decision Analysis,19(1-2): 3-13, 2012
刘晓, Yun Yang*, 姜元春, Preventing Temporal Violations in Scientific Workflows: Where and How，IEEE Transactions on Software Engineering, 37(6): 805-825, 2011
刘晓, Zhiwei Ni, Dong Yuan, 姜元春, A novel statistical time-series pattern based interval forecasting strategy for activity durations in workflow systems, Journal of Systems and Software, 84(3): 354-376, 2011
李旭军, 刘业政, 姜元春, 在线社交网络中群体互动行为的时间特征, 计算物理, 2015（录用）
刘业政, 杜亚楠, 姜元春, 杜非, 基于热度曲线分类建模的微博热门话题预测, 模式识别与人工智能, 28 (1): 27-71, 2015
张启平, 刘业政, 姜元春, 决策单元交叉效率的自适应群评价方法, 中国管理科学, 22 (11): 62-71, 2014
刘业政*, 姜元春, 张结魁, 证据信度的效用分析, 系统工程理论与实践, 3: 103-110, 2008 (中文版)
(刘业政*,姜元春, Jiekui Zhang, The Utility Analysis of Belief in Evidence Theory, Systems Engineering-Theory and Practice, 3, pp. 103-110, 2008 (英文版))
刘业政*, 姜元春, 林文龙, 基于模糊距离和神经网络的自适应群决策方法, 系统工程学报, 1: 28-35, 2008
姜元春*, 刘业政, 基于粗糙集与证据理论的决策规则合成方法研究, 系统仿真学报, 20(4): 951-955, 2008
（2）专著
刘业政, 姜元春, 张结魁, 网络消费者行为: 理论方法及应用, 科学出版社, 2011.2
Hai Wang, 刘业政, 姜元春, Shouhong Wang, Queuing Networks for Designing Shared Services. In: Wang, J. (Ed.), Encyclopedia of Business Analytics and Optimization, pp.1961-1966. Hershey, PA: IGI Global, 2014
（3）专利
姜元春，钱洋，杜非，刘业政等，基于项目使用次数的矩阵分解推荐方法，2016102645522（授权）
姜元春, 邵亮, 刘业政等, 一种考虑用户-作者关系建模的个性化搜索算法, 201510889763.0 （授权）
刘业政, 姜元春, 王锦坤等, 一种基于推荐概率融合的混合推荐方法, 201310637512.4 （授权）
刘业政, 王锦坤, 姜元春等, 一种基于全局评分信息的项目协同过滤推荐方法, 201410436669.5 （授权）
刘业政，宋颖欣，王锦坤，姜元春，孙见山，孙春华, 一种基于产品项目特征扩充的最近邻协同过滤方法, 2016105471486 （授权）
姜元春，杨露，刘业政，王锦坤，一种基于双向张量分解的群推荐方法，2016111685321（授权）
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