Abstract
Recommendation service could provided recommended project resources for interested preference to network users, has now been maturely used to site navigation, retrieval system in digital libraries and e-commerce etc. The article respectively introduced existing various recommendation algorithm, and analyzed the advantages and disadvantages of all kinds of algorithm, and came up with an adaptive recommendation algorithm based on the Bayesian network. The results of theoretical analysis and experiments indicated that the algorithm could make personalized recommendation for users in real-time online. Compared with other existing algorithms, this algorithm could give the recommendation set more quickly with higher precision and recall level.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Yang B, Zhao P (2011) Review of the art of recommendation algorithms. J Shanxi Univ (Nat Sci Ed) 34(3):337–350
Sarwar B, Karypis G, Konstan J (2005) Item-based collaborative filtering recommendation algorithms. In: Proceedings of 10th international World Wide Web conference, vol 239, pp 191–201
Bihang X (2010) A hybrid personal recommendation algorithm based on designated group interest. J Shanghai Univ (Nat Sci) 16:3–5
Tsamardinos I, Brown LE, Aliferis CF (2006) Themax-m in hill-climbing Bayesian network structure learning algorithm. Mach Learn 65(1):31–78
Guo Q, Wang Q (2010) A recommendation-system model of digital library and its realization based on web mining. Libr J l29:6
Pan X, Deng G-S, Liu J-G (2010) Effects of user tastes on personalized recommendation. Control Eng China 39(1):19–22
Xu M-Y, Wei Y-Q, Zhao J (2011) Incremental learning method of Bayesian classification combined with feedback information. J Comput Appl 9:12–13
Wang A-G, Li L, Yang J, Chen G (2011) An algorithm based on the Bayesian network for web page recommendation. J Shandong Univ 91:212–216
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag London
About this paper
Cite this paper
Xiao, J., Gao, J., Song, G. (2013). Adaptive Recommendation Algorithm Based on the Bayesian-Network. In: Du, W. (eds) Informatics and Management Science III. Lecture Notes in Electrical Engineering, vol 206. Springer, London. https://doi.org/10.1007/978-1-4471-4790-9_19
Download citation
DOI: https://doi.org/10.1007/978-1-4471-4790-9_19
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-4789-3
Online ISBN: 978-1-4471-4790-9
eBook Packages: EngineeringEngineering (R0)