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-  2017 

面向移动健康医疗系统的多层二分网络推荐算法
An improved recommendation algorithm for mobile health care system

DOI: 10.7523/j.issn.2095-6134.2017.01.015

Keywords: 移动健康医疗系统,多层二分网络,推荐算法
mobile health care system
,multi-bipartite network,recommendation algorithm

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Abstract:

摘要 移动健康医疗系统是信息搜索、精准服务和信息过滤的重要手段,有效提升现有医疗资源的使用效率。为提高健康资讯推荐效率和准确性,提出一种多层二分网络推荐算法,将用户评价标准扩展为“感兴趣”、“不感兴趣”和“未知”3种级别;同时,根据用户感兴趣的信息类别,将原有的“用户-信息”层改进为“用户-信息-类别”层,使置信度在移动医疗多层网络中迭代传播,优化分级医疗资源的使用效率。实验结果表明,多层二分网络推荐算法提高了移动健康医疗系统的服务效率。

References

[1]  <p> Deshpande M, Karypis G. Item-based top-N, recommendation algorithms[J]. ACM Transactions on Information Systems, 2014, 22(1):143-177.
[2]  Zhou T, Ren J, MEDO Matuo, et al. Bipartite network projection and personal recommendation[J]. Physical Review E, 2007, 76(4):70-80.
[3]  Fouss F, Pirotte A, Renders J M, et al. Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation[J]. Knowledge & Data Engineering IEEE Transactions on, 2007, 19(3):355-369.
[4]  Koren Y, Bell R, Volinsky C. Matrix factorization techniques for recommender systems[J]. IEEE Computer, 2009, 42(8):30-37.
[5]  Davis J, Goadrich M. The relationship between precision-recall and ROC curves[C]//Proceedings of the 23rd international conference on Machine learning. ACM, 2010:233-240.</p>
[6]  Yin F, Zhao X, Zhang X, et al. Improving accuracy and scalability of personal recommendation based on bipartite network projection[J]. Mathematical Problems in Engineering, 2014:823749.
[7]  Guo Q, Song W J, Hou L, et al. Effect of the time window on the heat-conduction information filtering model[J]. Physica A Statistical Mechanics & Its Applications, 2014, 401(5):15-21.
[8]  Javari A, Gharibshah J, Jalili M. Recommender systems based on collaborative filtering and resource allocation[J]. Social Network Analysis & Mining, 2014, 4(1):1-11.
[9]  Balabanovi?M, Shoham Y. Fab:content-based, collaborative recommendation[J]. Communications of the ACM, 1997, 40(3):66-72.
[10]  Pazzani M J, Billsus D. Content-based recommendation systems[C]//Springer-Verlag, LNCS, 2007,4321:325-341.
[11]  Zhang X M, Jiang S Y. Personalized recommendation algorithm based on weighted bipartite network[J]. Journal of Computer Applications, 2012, 32(3):654-653.
[12]  Sadja A, Tang J, Mihalov B, et al. System and method for providing recommendations to a user in a viewing social network:US, US 20120117167 A1. 2012.
[13]  Jamali M, Ester M. A transitivity aware matrix factorization model for recommendation in social networks[C]//IJCAI 2011, Proceedings of the International Joint Conference on Artificial Intelligence. Barcelona, Catalonia, Spain. 2011:2644-2649.
[14]  Schein A I, Popescul A, Ungar L H, et al. Methods and metrics for cold-start recommendations[C]//International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2002:253-260.
[15]  Miller B N, Albert I, Lam S K, et al. MovieLens unplugged:experiences with an occasionally connected recommender system[C]//International Conference on Intelligent User Interfaces. ACM, 2003:263-266.

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