计算机技术、控制技术 |
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基于增量图形模式匹配的动态冷启动推荐方法 |
张亚楠, 陈德运, 王莹洁, 刘宇鹏 |
1 .哈尔滨理工大学 计算机科学与技术博士后科研流动站,哈尔滨 150080
2 .哈尔滨理工大学 软件学院,哈尔滨 150040
3. 哈尔滨理工大学 计算机科学与技术学院
4. 烟台大学 计算机与控制工程学院,烟台264000 |
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Incremental graph pattern matching based dynamic recommendation method for cold-start user |
ZHANG Ya nan, CHEN De yun, WANG Ying jie, LIU Yu peng |
1. Post-doctoral Research Station of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080, China;
2. Software school,Harbin University of Science and Technology, Harbin 150040,China;
3. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150080,China;
4. School of computer and control engineering, YanTai University, YanTai 264000,China |
引用本文:
张亚楠, 陈德运, 王莹洁, 刘宇鹏. 基于增量图形模式匹配的动态冷启动推荐方法[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2017.02.025.
ZHANG Ya nan, CHEN De yun, WANG Ying jie, LIU Yu peng. Incremental graph pattern matching based dynamic recommendation method for cold-start user. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2017.02.025.
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[1] BOBADILLA J S, ORTEGA F, HERNANDO A, et al. A collaborative filtering approach to mitigate the new user cold start problem[J]. Knowledge-Based Systems, 2012, 26(1): 225-238.
[2] LIKA B, KOLOMVATSOS K, HADJIEFTHYMIADES S. Facing the cold start problem in recommender systems [J]. Expert Systems with Applications, 2014, 41(4): 2065-2073.
[3] REN Y L, LI G, ZHOU W L. PRICAI 2012: Trends in Artificial Intelligence [M]. Berlin: Springer, 2012:887-890.
[4] LING Y X, GUO D K, CAI F, et al. User-based Clustering with Top-N Recommendation on Cold-Start Problem[C]∥Proceedings of the 2013 3rd International Conference on Intelligent System Design and Engineering Applications. Hong Kong: IEEE Computer Society, 2013: 1585-1589.
[5] LOPS P, DE GEMMIS M, SEMERARO G. Recommender systems handbook [M]. Berlin Heidelberg: Springer, 2011: 73105.
[6] YIN H, CUI B, CHEN L, et al. A temporal context-aware model for user behavior modeling in social media systems [C]∥Proceedings of the 2014 ACM SIGMOD international Conference on Management of Data. Snowbird, USA: ACM, 2014: 1543-1554.
[7] WANG J, DE VRIES A P, REINDERS M J T. Unifying user-based and item-based collaborative filtering approaches by similarity fusion[C]∥Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. Washington, USA: ACM, 2006: 501-508.
[8] JAMALI M, ESTER M. A matrix factorization technique with trust propagation for recommendation in social networks [C]∥Proceedings of the 4th ACM Conference on Recommender Systems. Barcelona, Spain: ACM, 2010: 135-142.
[9] MA H, YANG H, LYU M R, et al. Sorec: social recommendation using probabilistic matrix factorization[C]∥Proceedings of the 17th ACM Conference on Information and Knowledge Management. Napa Valley, USA: ACM, 2008: 931-940.
[10] WU L, CHEN E H, LIU Q, et al. Leveraging tagging for neighborhoodaware probabilistic matrix factorization[C]∥Proceedings of the 21st ACM International Conference on Information and Knowledge Management. Maui Hawaii, USA: ACM, 2012: 1854-1858.
[11] KOREN Y. Collaborative filtering with temporal dynamics[J]. Communications of the ACM, 2010, 53(4): 89-97.
[12] REN L, GU J Z, XIA W W. An item-based collaborative filtering approach based on balanced rating prediction [C]∥Proceedings of 2011 International Conference on Multimedia Technology. Hangzhou: IEEE, 2011: 3405-3408.
[13] ZHAO W X, LI S, HE Y, et al. Connecting social media to e-commerce: cold-start product recommendation using microblogging information [J]. IEEE Transactions on Knowledge & Data Engineering, 2016, 28(5): 1147-1159.
[14] 李洋,陈毅恒,刘挺.微博信息传播预测研究综述[J].软件学报,2016(2): 247-263.
LI Y, CHEN YH, LIU T. Survey on predicting information propagation in microblogs[J]. Journal of Software, 2016,27(2): 247-263.
[15] 赵泽亚,贾岩涛,王元卓,等.大规模演化知识网络中的关联推理[J].计算机研究与发展,2016, 53(2):492-502.
ZHAO ZY, JIA YT, WANG YZ, et al. Link inference in large scale evolutionable knowledge network[J]. Journal of Computer Research and Development, 2016, 53(2): 492-502.
[16] REAFEE W, SALIM N, KHAN A. The power of implicit social relation in rating prediction of social recommender systems [J]. Plos One, 2016, 11(5):120.
[17] PENG F, LU J, WANG Y, et al. N-dimensional markov random field prior for cold-start recommendation [J]. Neurocomputing, 2016, 191(1): 187-199.
[18] MA H, KING I, LYU M R. Learning to recommend with social trust ensemble [C]∥Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval. Gold Coast, Australia: ACM, 2009: 203-210.
[19] KIM Y A, SONG H S. Strategies for predicting local trust based on trust propagation in social networks [J]. Knowledge-Based Systems, 2011, 24(8): 1360-1371.
[20] YUAN W W, GUAN D H, LEE Y K, et al. Improved trustaware recommender system using small-worldness of trust networks [J]. KnowledgeBased Systems, 2010, 23(3): 232-238.
[21] JIANG W J, WANG G J, WU J. Generating trusted graphs for trust evaluation in online social networks[J]. Future generation computer systems, 2014, 31(1): 48-58.
[22] LIU R R, LIU J G, JIA C X, et al. Personal recommendation via unequal resource allocation on bipartite networks [J]. Physica A: Statistical Mechanics and its Applications, 2010, 389(16): 3282-3289.
[23] GUHA R, KUMAR R, RAGHAVAN P, et al. Propagation of trust and distrust[C]∥ Proceedings Of The 13th International Conference on World Wide Web. New York, USA: ACM, 2004: 403-412.
[24] DENG S, HUANG L, XU G. Social network-based service recommendation with trust enhancement[J]. Expert Systems with Applications, 2014, 41(18):8075-8084.
[25] MORADI P, AHMADIAN S. A reliability-based recommendation method to improve trust-aware recommender systems [J]. Expert Systems with Applications, 2015, 42(21): 7386-7398.
[26] LE H S. Dealing with the new user cold-start problem in recommender systems: A comparative review[J]. Information Systems, 2014, 58(1): 87-104.
[27] WANG Y, YIN G, CAI Z, et al. A trust-based probabilistic recommendation model for social networks[J]. Journal of Network & Computer Applications, 2015, 55(1): 59-67.
[28] WANG Y, CAI Z, YIN G, et al. An Incentive Mechanism with privacy protection in mobile crowdsourcing systems[J]. Computer Networks, 2016, 102(1):157-171. |
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