SMALE实验室论文成果：推荐系统CSDN源码

摘要: 本贴列出实验室在推荐系统方向的一些工作. 主要目的是保存 bib 方便以后查阅与引用.

1. SCI 期刊论文

1.1 三支推荐开山之作, 基于隐式评价 (即是否购买).

引用次数 200+.

@article{ZhangMin2016Three,
 title   = {Three-way recommender systems based on random forests},
 author  = {Heng-Ru Zhang and Fan Min},
 journal = {Knowledge-Based Systems},
 year    = {2016},
 volume  = {91},
 pages   = {275--286},
 doi       = {10.1016/j.knosys.2015.06.019}
}
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1.2 ZhangMin2016Three 的姊妹篇, 基于显式评价 (即评分).

也是高被引.

@article{ZhangMin2017Regression,
 title	  = {Regression-based three-way recommendation},
 author  = {Heng-Ru Zhang and Fan Min and Bing Shi},
 journal = {Information Sciences},
 year    = {2017},
 volume  = {378},
 pages   = {444--461},
 doi     = {10.1016/j.ins.2016.03.019}
}
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1.3 引入了三支会话推荐问题，并设计了混合会话推荐（HTCR）算法

引用次数 0

@article{Xu2022Hybrid,
 author  = {Yuan-Yuan Xu and Shen-Ming Gu and Hua-Xiong Li and Fan Min},
 title   = {A hybrid approach to three-way conversational recommendation},
 journal = {Soft Computing},
 year    = {2022},
 pages   = {1--13},
 doi     = {10.1007/s00500-022-07416-x}
}
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1.4 设计了一种启发式概念格推荐方法

引用次数 0

@article{Liu2022Heuristic,
 author  = {Zhong-Hui Liu and Qi Zhao and Lu Zou and Wei-Hua Xu and Fan Min},
 title   = {A heuristic concept construction approach to collaborative recommendation},
 journal = {International Journal of Approximate Reasoning},
 year    = {2022},
 volume  = {146},
 pages   = {119--132},
 doi     = {10.1016/j.ijar.2022.04.004}
}
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1.5 提出了一种无需用户干预的高斯混合（MoG）模型来估计推荐系统的魔法边界

引用次数 1

@article{Zhang2022Mixture,
 author  = {Heng-Ru Zhang and Jie Qian and Hui-Lin Qu and Fan Min},
 title   = {A Mixture-of-Gaussians model for estimating the magic barrier of the recommender system},
 journal = {Applied Soft Computing},
 year    = {2022},
 volume  = {114},
 pages   = {108162},
 doi     = {10.1016/j.asoc.2021.108162}
}
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1.6 提出了一种高效的离群点去除算法，以提高训练数据的质量

引用次数 0

@article{Xu2022Improving,
 author  = {Yuan-Yuan Xu and Shen-Ming Gu and Fan Min},
 title   = {Improving recommendation quality through outlier removal},
 journal = {International Journal of Machine Learning and Cybernetics}, 
 year    = {2022},
 volume  = {13},
 number  = {7},
 pages   = {1819--1832},
 doi     = {10.1007/s13042-021-01490-7}
}
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1.7 提出了一种局部信息嵌入的增强slope one推荐算法

引用次数 0

@article{Zhang2019Esli,
 author  = {Heng-Ru Zhang and Yuan-Yuan Ma and Xin-Chao Yu and Fan Min},
 title   = {ESLI: Enhancing slope one recommendation through local information embedding},
 journal = {Plos one},
 year    = {2019},
 volume  = {14},
 number  = {10},
 pages   = {e0222702},  
 doi     = {10.1371/journal.pone.0222702}
}
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1.8 将带有情感的评论引入矩阵分解模型，提高推荐的可靠性（SBMF+R）

引用次数 47

@article{Shen2019Sentiment,
 author  = {Rong-Ping Shen and Heng-Ru Zhang and Hong Yu and Fan Min},
 title   = {Sentiment based matrix factorization with reliability for recommendation},
 journal = {Expert Systems with Applications},
 year    = {2019},
 volume  = {135},
 pages   = {249--258},
 doi     = {10.1016/j.eswa.2019.06.001}
}
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1.9 提出新的相似性度量–多通道特征向量（MCFV），并利用该度量设计了新的推荐算法

引用次数 25

@article{Zhang2019Efficient,
 author  = {Heng-Ru Zhang and Fan Min and Zhi-Heng Zhang and Song Wang},
 title   = {Efficient collaborative filtering recommendations with multi-channel feature vectors},
 journal = {International Journal of Machine Learning and Cybernetics},
 year    = {2019},
 volume  = {10},
 number  = {5},
 pages   = {1165--1172},
 doi     = {10.1007/s13042-018-0795-8}
}
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1.10 提出推荐算法集成的适应性机制（AMRE）。AMRE由三部分组成，包括一组代理、一个奖励函数和一个轮询机制。

引用次数 1

@article{Huang2019Adaptive,
 author  = {Qi Huang and Yuan-Yuan Xu and Yong Chen and Heng-Ru Zhang and Fan Min},
 title   = {An adaptive mechanism for recommendation algorithm Ensemble},
 journal = {IEEE Access},
 year    = {2019},
 volume  = {7},
 pages   = {10331--10342},
 doi     = {10.1109/ACCESS.2019.2891561}
}
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1.11 首次在魔法边界估计上提出理论模型，设计了三个正态分布模型来估计推荐系统的魔法边界

引用次数 5

@article{Zhang2018Magic,
 author  = {Heng-Ru Zhang and Fan Min and Yan-Xue Wu and Zhuo-Lin Fu and Lei Gao},
 title   = {Magic barrier estimation models for recommended systems under normal distribution},
 journal = {Applied Intelligence},
 year    = {2018},
 volume  = {48},
 number  = {12},
 pages   = {4678--4693},
 doi     = {10.1007/s10489-018-1237-8}
}
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1.12 结合三角和Jaccard相似度，提出了一种新的推荐方法

引用次数 56

@article{Sun2017Integrating,
 author  = {Shuang-Bo Sun and Zhi-Heng Zhang and Xin-Ling Dong and Heng-Ru Zhang and Tong-Jun Li and Lin Zhang and Fan Min},
 title   = {Integrating Triangle and Jaccard similarities for recommendation},
 journal = {PloS one},
 year    = {2017},
 volume  = {12},
 number  = {8},
 pages   = {1--16},
 doi     = {10.1371/journal.pone.0183570}
}
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2. 国际会议论文

3. 核心期刊论文

3.1 提出了一种融合直接和间接的用户非对称信任关系的推荐算法(ATRec)

引用次数 3

@article{Zhang2018Recommendation,
 author  = {Zi-Yin Zhang and Heng-Ru Zhang and Yuan-Yuan Xu and Qin Qin},
 title   = {Recommendation algorithm combining user's asymmetric trust relationships},
 journal = {Computer Science},
 year    = {2018},
 volume  = {45},
 number  = {10},
 pages   = {37--42},
 doi     = {10.11896/j.issn.1002-137X.2018.10.007}
}
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3.2 为解决评分系统中存在的数据稀疏问题，提出一种内涵粗糙三支概念以及基于它的个性化推荐方案

引用次数 0

@article{Liu2022Three,
 author  = {Zhong-Hui Liu and Xin Li and Fan Min},
 title   = {Three-wayconcept with rough intent and its application in personalized recommendation},
 journal = {Journal of Northwest University(Natural Science Edition)},
 year    = {2022},
 pages   = {1--10},
 doi     = {10.16152/j.cnki.xdxbzr.2022-05-005}
}
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3.3 介绍了三元概念的构建，并将应用于社会化推荐

引用次数 1

@article{Liu2021Heuristic
 author  = {Zhong-Hui Liu and Qi Zhao and Lu Zou and Fan Min},
 title   = {Heuristic construction of triadic concept and its application in social recommendation},
 journal = {Computer Science},
 year    = {2021},
 pages   = {234--240},
 issue   = {06},
 doi     = {10.11896/jsjkx.200500136}
}
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3.4 提出一种基于启发式概念构造的组推荐方法

引用次数 3

@article{Liu2019Group,
 author  = {Zhong-Hui Liu and Lu Zou and Mei Yang and Fan Min},
 title   = {Group recommendation with concept of heuristic construction},
 journal = {Journal of Frontiers of Computer Science and Technology},
 year    = {2019}
 volume  = {14},
 number  = {4},
 pages   = {703--711},
 doi     = {10.3778/j.issn.1673-9418.1905012}
}
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3.5 提出一种可解释性泛化矩阵分解推荐算法

引用次数 0

@article{Lv2022An,
 author  = {Ya-Lan Lv and Yuan-Yuan Xu and Heng-Ru Zhang},
 title   = {An explainable generalized matrix factorization recommendation algorithm},
 journal = {Journal of Nanjing University(Natural Sciences)},
 year    = {2022}，
 volume  = {58},
 number  = {1},
 pages   = {135--142},
 doi     = {10.13232/j.cnki.jnju.2022.01.013}
}
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3.6 为同时提高推荐系统的准确度和效率, 提出了一种多通道特征向量的新三角距离推荐算法

引用次数 0

@article{Lv2021Efficient,
 author  = {Ya-Lan Lv and Heng-Ru Zhang and Qin Qin and Yuan-Yuan Xu},
 title   = {Efficient Recommendation of New Triangular Distance for Multi-channel Feature Vectors},
 journal = {Journal of Suthwest University(Natural Science)},
 year    = {2021},
 volume  = {43},
 number  = {10},
 pages   = {19--28},
 doi     = {10.13718/j.cnki.xdzk.2021.10.003}
}
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3.7 针对油气生产中的抽油机井参数优化问题，提出了一种基于抽油机井生产调控、维护措施数据的抽油机井生产参数优化的粒计算方法

引用次数 1

@article{Zhang2020Granular,
 author  = {Heng-Ru Zhang and Ke-Lin Zhu and Yuan-Yuan Xu and Ying Qiao},
 title   = {Granular computing for pumping well parameter optimization},
 journal = {Journal of Southwest Petroleum University (Science & Technology Edition)},
 year    = {2020}，
 volume  = {42},
 number  = {6},
 pages   = {115},
 doi     = {10.11885/j.issn.1674-5086.2020.05.29.02}
}
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3.8 提出基于信任传递机制的三支推荐算法

引用次数 4

@article{Qin2020Three,
 author  = {Qin Qin and Heng-Ru Zhang},
 title   = {Three-way recommendation based on trust transfer mechanism},
 journal = {Pattern Recognition and Artificial Intelligence},
 year    = {2020}，
 volume  = {33},
 number  = {7},
 pages   = {600--609},
 doi     = {10.16451/j.cnki.issn1003-6059.202007003}
}
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3.9 模拟现实电子商务推荐场景，设计三支交互推荐模型，提出结合流行度区间和 M-distance k 近邻的混合推荐算法

引用次数 6

@article{Xu2019Three,
 author  = {Yuan-Yuan Xu and Heng-Ru Zhang and Fan Min and Yu-Ting Huang},
 title   = {Three-way interactive recommendation},
 journal = {Journal of Nanjing University (Natural Sciences)},
 year    = {2019},
 volume  = {55},
 number  = {6},
 pages   = {973--983},
 doi     = {10.13232/j.cnki.jnju.2019.06.010}
}
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