Abstract
As the development of information technology and intelligent tutoring, web-based learning has been widely used nowadays to help people acquire knowledge in a flexible way. Especially, web-based learning services can greatly facilitate farmers to gain knowledge on farming. It is observed that learning goals and preferences tend to be localized for farming knowledge due to similar climate and soil conditions in an area. Therefore, geographical information can be utilized to recommend agricultural learning resources. In this paper, an agricultural learning resource recommendation approach is proposed using agent-based simulation that takes geographical information into account. The agent simulation environment is introduced. A distance-aware agent reputation model is presented. A multi-agent collaborative recommendation approach is proposed. Simulation experiments are conducted for the evaluation of the proposed approach. The results show good performance of it.
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
Similar content being viewed by others
References
Chen, W., Zeng, Q., Wenyin, L., Hao, T.: A user reputation model for a user-interactive question answering system. Concurrency Comput. Prac. Exp. 19(15), 2091–2103 (2007). http://dx.doi.org/10.1002/cpe.1142
King, I., Ng, C.H., Sia, K.C.: Distributed content-based visual information retrieval system on peer-to-peer networks. ACM Trans. Inf. Syst. 22(3), 477–501 (2004). http://doi.acm.org/10.1145/1010614.1010619
Mandula, K., Meday, S.R., Muralidharan, V., Parupalli, R.: A student centric approach for mobile learning video content development and instruction design. In: 2013 15th International Conference on Advanced Communication Technology (ICACT), pp. 386–390. IEEE (2013)
Niinivaara, O.: Agent-based recommender systems. Department of Computer Science, University of Helsinki, pp. 1–48 (2004)
Qureshi, B., Min, G., Kouvatsos, D.: A distributed reputation and trust management scheme for mobile peer-to-peer networks. Comput. Commun. 35(5), 608–618 (2012)
Sabater, J., Sierra, C.: Reputation and social network analysis in multi-agent systems. In: The First International Joint Conference on Autonomous Agents & Multiagent Systems, AAMAS 2002, Proceedings, Bologna, Italy, 15–19 July 2002, pp. 475–482. ACM (2002). http://doi.acm.org/10.1145/544741.544854
Zou, D., Xie, H., Wong, T.-L., Rao, Y., Wang, F.L., Wu, Q.: Predicting pre-knowledge on vocabulary from e-learning assignments for language learners. In: Gong, Z., Chiu, Dickson, K.,W., Zou, D. (eds.) ICWL 2015. LNCS, vol. 9584, pp. 111–117. Springer, Heidelberg (2016). doi:10.1007/978-3-319-32865-2_12
Acknowledgment
This paper is supported by the monitoring statistics Project on Agricultural and rural resources “Agricultural Monitoring, Early Warning and Informatization” funded by Ministry of Agriculture of China, the Innovative Talents Project “Key Techniques of Main Agricultural Products Market Monitoring And Early Warning” funded by Ministry of Agriculture of China, the Science and Technology Innovation Project “Innovation Team on Agricultural Production Management Digitization Technology” (CAAS-ASTIP-2015-AII-02) funded by Chinese Academy of Agricultural Sciences, and sub-project “Agricultural Data Collection Methods and Technology Analysis” of project of Ministry of Agricultural of China “Monitoring and Statistics Fund for Agriculture and Rural Resources”.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Chen, W., Li, Z. (2017). Agent-Based Simulation for Agricultural Learning Resource Recommendation Based on Geographical Similarities. In: Wu, TT., Gennari, R., Huang, YM., Xie, H., Cao, Y. (eds) Emerging Technologies for Education. SETE 2016. Lecture Notes in Computer Science(), vol 10108. Springer, Cham. https://doi.org/10.1007/978-3-319-52836-6_59
Download citation
DOI: https://doi.org/10.1007/978-3-319-52836-6_59
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52835-9
Online ISBN: 978-3-319-52836-6
eBook Packages: Computer ScienceComputer Science (R0)