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Tomasz Neumann
 

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TransNav, Faculty of Navigation
Gdynia Maritime University
3, John Paul II Avenue
81-345 Gdynia, POLAND
www http://www.transnav.eu
e-mail transnav@am.gdynia.pl
Applied Research of Route Similarity Analysis Based on Association Rules
1 Shanghai Maritime University, Shanghai, China
ABSTRACT: In recent years, with the development of information technology, businesses have accumulated a lot of useful historical data, as the shipping industry does. These data can be found deposited a large number of "knowledge", for example, Shipping records for historical information, Ship-Port relations information, Ship-ship relations information, Port & shipping route relations, Shipping route information. It can provide intellectual support to shipping informatization development. Association rules in data mining technology is one of important technologies. The technology, based on statistical methods, can mine the associated and implied "knowledge" from data warehouse ,which has a large number of accumulated data. Apart from this, the technology can also play an important role in the prediction. In this paper, based on FP-growth algorithm, we improve it forming Relevent ships routes. From the prevalent perspective of data mining, deal with the corresponding vessels' dynamic information, acquired from the AIS, such as data collection, data statistics. On this basis, get the ship-port relation and ship-ship relation after a certain level of data analysis, processing, handing. Furthermore, this paper use the numerous historical ship-port relation and ship-ship relation to build a mathematical model on the ship-port and ship-ship relation. And use the improved association algorithm, FP-growth algorithm, to acquire the strong association rules between ship-port and ship-ship, and eventually mine the similarity of the ship route. Main points of this paper as follows: Collect ,count and check the data, which is from ship dynamic information; Establish the mathematical model between ship-port and ship-ship relation; Improve the algorithm; Analyse the similarity of ship route more accurately using the improved algorithm.
REFERENCES
MA Xu-hui, Zhang A-hong. Association Rules Generated By the FP Tree Depth-First Algorithm. Computer Knowledge and Technology, 2010, 13: 058
HUI Liang, QIAN Xue-zhong. Non-check mining algorithm of maximum frequent patterns in association rules based on FP-tree. Journal of Computer Applications, 2010, 07: 064
YAN Wei, BAI Wen-yang, ZHANG Yan. Hiding Associa-tion Rules with FP-Tree Based Transaction Dataset Recon-strucion. Department of Computer Science and Technolo-gy, 2008
JI Xian-biao, SHAO Zhe-ping, PAN Jia-cai, et al. Develop-ment of distributed data collection system of AIS infor-mation and key techniques[J].Journal of Shanghai Mari-time University, 2007, 28(3): 28-31
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Citation note:
Xiang Z., Liu R., Hu Q., Shi C.J.: Applied Research of Route Similarity Analysis Based on Association Rules. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 6, No. 2, pp. 181-185, 2012

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