Abstract
In this paper, we try to systematically study how to perform doctor recommendation in medical social networks (MSNs). Specifically, employing a real-world medical dataset as the source in our work, we propose iBole, a novel hybrid multi-layer architecture, to solve this problem. First, we mine doctor-patient relationships/ties via a time-constraint probability factor graph model (TPFG). Second, we extract network features for ranking nodes. Finally, we propose RWRModel, a doctor recommendation model via the random walk with restart method. Our real-world experiments validate the effectiveness of the proposed methods. Experimental results show that we obtain good accuracy in mining doctor-patient relationships from the network, and the doctor recommendation performance is better than that of the baseline algorithms: traditional Ranking SVM (RSVM) and the individual doctor recommendation model (IDR-Model). The results of our RWR-Model are more reasonable and satisfactory than those of the baseline approaches.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Baeza-Yates R, Ribeiro-Neto B. Modern Information Retrieval. Addison Wesley, 1999, pp.98-105.
Salton G, Wong A, Yang C S. A vector pace model for automatic indexing. Communications of the ACM, 1975, 18(11): 613–620.
Wang C, Han J W, Jia Y T, Tang J, Zhang D, Yu Y T, Guo J Y. Mining advisor-advisee relationships from research publication networks. In Proc. the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 2010, pp.203-212.
Yang Z, Tang J, Zhang J, Li J Z, Gao B. Topic-level random walk through probabilistic model. In Lecture Notes in Computer Science 5446, Li Q, Feng L, Pei J, Wang S X, Zhou X F, Zhu Q M (eds.), Springer Berlin Heidelberg, 2009, pp.162-173.
Macdonald C, Ounis I. Voting for candidates: Adapting data fusion techniques for an expert search task. In Proc. the 15th ACM International Conference on Information and Knowledge Management, November 2006, pp.387-396.
Gong J B, Tang J, Fong A C M. ACTPred: Activity prediction in mobile social networks. Tsinghua Science and Technology, 2014, 19(3): 265–274.
Hu L, Song G H, Xie Z Z, Zhao K. Personalized recommendation algorithm based on preference features. Tsinghua Science and Technology, 2014, 19(3): 293–299.
Shen Y L, Jin R M. Learning personal + social latent factor model for social recommendation. In Proc. the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2012, pp.1303-1311.
Salakhutdinov R, Mnih A, Hinton G. Restricted Boltzmann machines for collaborative filtering. In Proc. the 24th International Conference on Machine Learning, June 2007, pp.791-798.
Gong J B, Sun S T. Individual doctor recommendation model on medical social network. In Proc. the 7th ADMA, Part II, December 2011, pp.69-81.
Yang Z, Tang J, Wang B, Guo J Y, Li J Z, Chen S C. Expert2Bólè: From expert finding to Bólè search. In Proc. the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 1, 2009, pp.1-4.
Tang J, Sun J M, Wang C, Yang Z. Social influence analysis in large-scale networks. In Proc. the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, June 28-July 1, 2009, pp.807-816.
Kuhn H W. The Hungarian method for the assignment problem. Naval Research Logistics Quarterly, 1955, 2(1/2): 83–97.
Karimzadehgan M, Zhai C X, Belford G. Multi-aspect expertise matching for review assignment. In Proc. the 17th ACM Conference on Information and Knowledge Management, October 2008, pp.1113-1122.
Mimno D, McCallum A. Expertise modeling for matching papers with reviewers. In Proc. the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2007, pp.500-509.
Karimzadehgan M, Zhai C X. Constrained multi-aspect expertise matching for committee review assignment. In Proc. the 18th ACM Conference on Information and Knowledge Management, November 2009, pp.1697-1700.
Hartvigsen D, Wei J C, Czuchlewski R. The conference paper-reviewer assignment problem. Decision Sciences, 1999, 30(3): 865–876.
Tang J, Wu S, Sun J M, Su H. Cross-domain collaboration recommendation. In Proc. the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2012, pp.1285-1293.
Küçüktunç O, Saule E, Kaya K, Çatalyürek Ü V. Diversifying citation recommendations. ACM Transactions on Intelligent Systems and Technology, 2015, 5(4): 55:1–55:21
Tang J, Jin R, Zhang J. A topic modeling approach and its integration into the random walk framework for academic search. In Proc. the 8th ICDM, December 2008, pp.1055-1060.
Feng W, Wang J Y. Incorporating heterogeneous information for personalized tag recommendation in social tagging systems. In Proc. the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2012, pp.1276-1284.
Kschischang F R, Frey B J, Loeliger H A. Factor graphs and the sum-product algorithm. IEEE Transactions on Information Theory, 2001, 47(2): 498–519.
Tang J, Zhang J, Yao L M, Li J Z, Zhang L, Su Z. Arnet-Miner: Extraction and mining of academic social networks. In Proc. the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2008, pp.990-998.
Tang J, Fong A C M, Wang B, Zhang J. A unified probabilistic framework for name disambiguation in digital library. IEEE Transactions on Knowledge and Data Engineering, 2012, 24(6): 975–987.
Gong J B, Lu S L, Wang R, Cui L. PDhms: Pulse diagnosis via wearable healthcare sensor network. In Proc. the 2011 IEEE International Conference on Communications, June 2011.
Joachims T. Training linear SVMs in linear time. In Proc. the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 2006, pp.217-226.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Gong, JB., Wang, LL., Sun, ST. et al. iBole: A Hybrid Multi-Layer Architecture for Doctor Recommendation in Medical Social Networks. J. Comput. Sci. Technol. 30, 1073–1081 (2015). https://doi.org/10.1007/s11390-015-1583-5
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11390-015-1583-5