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Research and Application of Machine Learning on Geographic Information System

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DOI: 10.23977/jaip.2016.11006 | Downloads: 58 | Views: 6908


Zhenjiang Dong 1, Peng Yang 2, Zhicheng Ma 2, Yongbiao Chen 1


1 Shanghai Jiao Tong University, Shanghai, China
2 Gansu State Grid Information & Telecommunication Co., Ltd.629 East Xijin Road, Qilihe, Lanzhou, Gansu Province, China

Corresponding Author

Zhenjiang Dong


In the big data era, an information system that is able to flexibly scale out, store mass data and quickly response to concurrent requests is particularly important. Despite the mature mining technologies on structured data, the utilization of unstructured data is still inadequate which results in the waste of data sources. Under this circumstance, this paper adopts machine-learning technologies to build a salable information system by analyzing Geographical landform data.


Machine Learning; NoSQL Database; Neural Network; Recommender System; Collaborative Filtering


Zhenjiang, D. , Peng, Y. , Zhicheng, M. and Yongbiao C. (2016) Research and Application of Machine Learning on Geographic Information System. Journal of Artificial Intelligence Practice (2016) 1: 30-35.


[1] Kuota Chan. On the Subdivisions of the Red Beds of South-Eastern China[J]. Bulletin of the Geological Society of China, 1938, 18:315-316.
[2] DeCandia G, Hastorun D, Jampani M, et al. Dynamo: amazon's highly available key-value store[C]. ACM SIGOPS Operating Systems Review, 2007, 41(6): 205-220.
[3] Chang F, Dean J, Ghemawat S, et al. Bigtable: A distributed storage system for structured data[C]. ACM Transactions on Computer Systems (TOCS), 2008, 26(2): 4.
[4] Mitchell TM. The discipline of machine learning[M]. Carnegie Mellon University, School of Computer Science, Machine Learning Department, 2006.
[5] Werbos P. Beyond regression: New tools for prediction and analysis in the behavioral sciences[M]. 1974.
[6] Fukushima K. Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position[C]. Biological cybernetics, 1980, 36(4): 193-202.

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