Association Pattern Discovery of Import Export Items in Ethiopia

Mezgeb Manaye Gebru

Abstract


This paper examines the application of data mining to detect association pattern of customs administration data with market price and currency rate exchange in Ethiopia. The association rule method of data mining is used in this paper to generate the interesting pattern from the data. This study was done to identify the relationships between attributes of custom data and market price to clearly understand the nature of import-export items in Ethiopia. The results of the experiments carried out using association rules revealed that the technique of data mining is applicable to generate knowledge from import and export items in custom administration. Algorithms such as Apriori, Tertius, PredictiveApriori and FliteredApriori were used to generate the associations. One of the resulting associations indicates that there is a strong link between market price and textiles imported. The implication of this research finding is that it clearly identified the association of import-export items with the market price and the effects of those items on the market price and currency rate in Ethiopia.


Keywords


Data mining; Association rule; Weka; Association pattern; Apriori; Tertius; PredictiveApriori; FliteredApriori; Algorithm.

Full Text:

PDF

References


Alaaeldin M. Hafez, “Knowledge Discovery in Databases Alexandria University.” Department of Computer Science and Automatic Control Faculty of Engineering Alexandria University, 2008.

A. Larson and P. Sheth, “Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases.” Published by ACM Computing Surveys (CSUR), 1990.

A. Savasere, E. Omiecinski and S. Navathe. “An Efficient Algorithm for Mining Association Rules in large Databases," Proc. 21st Int’l, 1995, Conf. of Very Large Data Bases.

A. Silberschatz and A. Tuzhilin, “What makes patterns interesting in knowledge discovery systems.” IEEE Trans. on Knowledge and Data Eng., 8, 6, 1996.

Baeza-Yates, R. and Ribeiro-Neto, B.” Modern Information Retrieval.” Harlow, England: Addison Wesley, 1999.

Berry, M and Linoff, G. “Mastering Data Mining: The Art of Science of Customer Relationship Management.” John Willy and Sons Inc, New York, 2000.

Bigus, J.P. “Data Mining with Neural networks in Solving Business Problems-From Application to Development to Decision Support.” New York: McGraw-Hill, 1996.

Chris Clifton,GaryGengo, “Developing custom intrusion detection filters using data mining.” MILCOM. 21st Century Military Communications Conference Proceedings, 2000.

Chris Rygielski, Jyun-Cheng Wang and David C. Yen.”Data mining techniques for customer relationship management.”Technology in Society 24, Elsevier Science Ltd, 2000.

David L. Olson and Dursun Delen. “Advanced Data Mining Techniques.” Verlag Berlin Heidelberg: Springer, 2008.

Deogun, Jitender S. (2001) “Data Mining: research Trends, Challenges, and Applications.” [On-line] Available: http://citeseer.nj.nec.com/deogun97data.html,

D.Hawkins, “Identification of outliers”. London, Chapman and Hall, 1980.

D Pyle, “Data Preparation for Data Mining” Morgan Kaufmann Inc. ISBN 1-55860-529-0, 1999.

D Romano, “Data Mining Leading Edge: Insurance & Banking.” in Proceedings of Knowledge Discovery and Data Mining, Unicom, Brunel University, 1997

ER Grilli, “Primary commodity prices, manufactured goods prices, and the terms of trade of developing countries”. World Bank Economic Review, 1988, vol. 2, issue 1, 1-47. Date: 1988.

Fayyad, U. M., G. P. Shapiro, P. Smyth, “From Data Mining to Knowledge Discovery in Databases”, 0738-4602-1996, AI Magazine (Fall 1996): 37–53, 1996.

Fernando Crespoa, Richard Weberb , “A methodology for dynamic data mining based on fuzzy clustering”, Fuzzy Sets and Systems Volume 150, Issue 2, Pages 267-284 ,1 March 2005.

Han, Jiawei and Kamber, Micheline (2001). "Data Mining: Concepts and Techniques and Applications“. San Fransisico; Morgan Kufman Publishers.

Hailegiorgis Biramo Allaro, “The Impact of Trade Liberalization on the Ethiopia's Trade Balance American”. Journal of Economics 2(5): 75-81 DOI: 10.5923/j.economics.20120205.02, 2012.

Han,G.Karypis, and Kumar “Scalable parallel data mining for association rule”. IEEE transactions on knowledge and data engineering, 2000.

Forrester Wave “Predictive Analytics and Data Mining Solutions”, Whitepaper, [on line] http://www.rosebt.com/1/post/2012/06/predictive-analytics-and-data-mining-wave-2010.html,2010.

H. Liu, F. Hussain, C. Lim, M. Dash.” Discretization: An Enabling Technique”. Data Mining and Knowledge Discovery 6:4 393-423, 2002.

James D. Fearon, “Primary Commodity Exports and Civil War”, Journal of Conflict Resolution (J CONFLICT RESOLUT) Department of Political Science. Stanford University.2013.

Jerome H. Friedman, “Data Mining and Statistics: What's the Connection?” Int'l Conf. Scientific and Statistical Database Management. IEEE Computer Society. Friedman, Jerome H. 1998.

Jiawei Han, Micheline Kamber, “Data Mining: Concepts and Techniques”, Morgan Kaufmann Publishers, Champaign: CS497JH, fall 2001.

Justin Zake, “Customs Administration Reform and Modernization in Anglophone Africa—Early 1990s to Mid-2010”, [on line] https://www.imf.org/.../Customs-Administration-Reform-and-Modernization-in-anglo, August 1, 2011.

Jordi Galí and Tommaso Monacelli, “Monetary Policy and Exchange Rate Volatility in a Small Open Economy”, IGIER, Universit`a Bocconi and CEPR. First version received November 2002; final version accepted October 2004 (Eds.).

Laporte, “Risk management systems: using data mining in developing countries customs administrations”, World Customs Journal, 2011.

Levin, Nissan and Zahavi, Jacob, “Data Mining”, Tel Aviv University. December 1999.

Li Yan-hai, Sun lin-yan, “Study and Applications of Data Mining to the Structure Risk Analysis of Customs Declaration cargo”, e-Business Engineering, ICEBE IEEE International Conference on 2005.

L. Breiman, J.H. Friedman, R.A.Olshen, and C.J. Stone, “Classification and Regression Trees”. Wadsworth, Belmont, 1997.

Maimon, Oded, kandel, Abe and Last, Mark. “Information Theoretic Fuzzy Approach to Knowledge Discovery in Databases”. Available: http://www.csee.usf.edu/~mlast/papers/wsc_f2.pdf, 2002.

Maria Halkidi, “Quality assessment and Uncertainty Handling in Data Mining Process” Available: http://www.edbt2000.unikonstanz. de/phd-workshop/papers/Halkidi.pdf, 2000.

Mark Brown, John Brocklebank, “data mining”, SAS Institute Inc., 1998.

Maurizio Lenzerini, "Data Integration: A Theoretical Perspective" Dipartimento di Informatica e Sistemistica Universit `a di Roma “La Sapienza” Via Salaria 113, I00198 Roma, Italy, 2002.

MJA Berry, John Willey & Sons,” Data mining techniques: for marketing, sales, and customer support” ISBN: 978-0-471-17980-1. Jun 1997.

M. O. Mansur, Mohd. Noor Md. Sap,”Outlier Detection Technique in Data Mining:” A Research Perspective, 2005.

M. S. Chen, J. Han, P. S. Yu. , “Data mining: An overview from a database perspective.” IEEE Trans. on Knowledge and Data Eng., 8, 6, pp. 866–884, 1996.

Moghadam, M. B. and Rohanizadeh, S. S., “A Proposed Data Mining Methodology and its Application to Industrial Procedures”. Journal of Industrial Engineering 4 pp 37-50., 2009.

Narasimha Raju Alluri, “Evaluation of data mining methods to support data warehouse administration and montoring in SAP business warehouse”, Faculty of Business Applications of Computer Science. University of applied sciences - furtwangen. 2005.

Óscar Marbán, Gonzalo Mariscal and Javier Segovia “A Data Mining & Knowledge Discovery Process Model. In Data Mining and Knowledge Discovery in Real Life Applications” Book edited by: Julio Ponce and Adem Karahoca, ISBN 978-3-902613-53-0, pp. 438-453, I-Tech, Vienna, Austria, February 2009.

Padhraic Smyth, “Breaking Out of the Black-Box: Research Challenges in Data Mining”. June 2001.

Palous, Jiri (Nd), “Machine Learning and Data Mining. Prague: Gerstner Laboratory for Intelligent Decision Making and Control” .Czech Technical University. Available: http://citeseer.nj.nec.com/506615.html, 2001.

Paul R. Krugman, “Strategic trade policy and the new International economics”, Available:https://econpapers.repec.org/bookchap/mtptitles/0262610450.htm 2008.

Paul Dorosh and Hashim Ahmed, “Foreign Exchange Rationing, Wheat Markets and Food Security in Ethiopia, Development Strategy and Governance Division,” International Food Policy Research Institute – Ethiopia Strategy Support Program 2, Ethiopia, October 2009.

Philip K. chan,”Distributed data mining in credit card fraud detection”, Submitted to IEEE Intelligent Systems' Special Issue on Data Mining, 1999.

P. Smyth, R. M. Goodman, “Rule induction using information theory.” Proc. Intl. Conference on Knowledge Discovery and Data Mining, 159–176, 1991.

Paola Britos et al, “Tool Selection Methodology in Data Mining”, Intelligent Systems Laboratory. School of Engineering. University of Buenos Aires.2006.

Raghavan, V.V; Deogun, J.S. and Sever, H. “Knowledge Discovery and Data Mining: Introduction”. Journal of American Society for Information Science, Vol. 49, 1998.

Rea, Allan. “Data Mining: an introduction Student Notes”. Available: http://www.pcc.qub.ac.uk/tec/courses/datamining/stu_notes/dm_book_1.html 2001.

R. Agrawal, R. Srikant , “Fast algorithms for mining association rules”. Proc. 20th Intl. Conference on Very Large Databases, 487–499, 1994.

R. Agrawal, T. Imielinski, A. Swami., “Mining association rules between sets of items in a large database.” Proc. ACM SIGMOD Intl. Conference on Management of Data,pp. 207–216, 1993.

R. Agrawal and J.C. Shafer, “Parallel Mining of Association Rules,” IEEE Trans. On Knowledge and Data Eng., 8(6):962-969, December 1996.

R. Agrawal and R. Srikant, "Mining Sequential Patterns", In Proc. 11th Intl. Conf. On Data Engineering, Taipi, Taiwan, March 1995.

R. Garner WEKA: “The Waikato Environment for Knowledge Analysis.”

Department of Computer Science, University of Waikato, Hamilton. 2005

Refas, Salim, and Thomas Cantens, “Why does cargo spend weeks in African Ports? The case of Doula, Cameroon”, Policy Research Working Paper Series 5565, The World Bank, 2011.

Rüdiger Wirth, Jochen Hipp “CRISP-DM: Towards a Standard Process Model for Data Mining”, DaimlerChrysler Research & Technology FT3/KL. PO BOX 2360 89013 Ulm, Germany ruediger.wirth@daimlerchrysler.com. Jochen Hipp. Wilhelm-Schickard-Institute, University of Tübingen. Sand 13, 72076 Tübingen, Germany.2000.

Santos-Paulino, A and A. P. Thirlwall., “The Impact of Trade Liberalization on Exports, Imports and the balance of Payments of Developing Countries," Economic Journal, Royal Economic Society, 114(493), F50-F72, 02. 2004.

Sandeep Slave and Mathew Ninan, “Managing Data Quality”, Amrita University Publication, 2005.

Silberschhatz, Avi&Tuzhilns, Alexander. “What Makes Patterns Interesting In Knowledge Discovery System”. New York University. Available: http://citeseer.nj.nec.com/silberschatz96what.html, 1996.

S. Brin et al., “Dynamic Itemset Counting and Implication Rules for Market Basket Data,” Proc. ACM SIGMOD Conf. Management of Data, ACM Press, New York, 1997, pp. 255–264, 1997.

S. B. Kotsiantis, D. Kanellopoulos and P. E. Pintelas, “Data Preprocessing for Supervised Leaning”, International Journal Of Computer Science Volume 1 Number 2 2006 Issn 1306-4428, 2006.

Tobias Scheffer, “Finding Association Rules that Trade Support Optimally Against Confidence”. Humboldt-Universität zu Berlin, Department of Computer Science. Unter den Linden 6, 10099 Berlin, Germany scheffer@informatik.hu-berlin.de. August 9, 2004.

Herbert A. Edelstein. “Introduction to Data Mining and Knowledge Discovery”. Two Crows Corporation, Third Edition, 1999.

Weiyang Lin et al, “Efficient Adaptive support Association rule Mining for Recommender System”, Kluwer Academic Publisher, 2001.

Ian H. Witten and Frank, Eibe, “Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations”, 3rd edition, The Morgan Kaufmann Series in Data Management Systems, 2000.

Wrobel, S. “Inductive logic programming for knowledge discovery in databases. Relational Data Mining”, European Workshop on Logics in Artificial Intelligence JELIA 2006.

X. Wu et al, “Top 10 algorithms in data mining”, IEEE. International, 2008.

Zaki, M., “Generating non-redundant association rules”. Proceedings of the International Conference on Knowledge Discovery and Data Mining, 2005.

ELIAS A. ALI, “The Effect of Depreciation of Birr on Major Export Products of Ethiopia: The Case of Hides and Skins”, economics. Issue Date: 26-Jun-2012. Publisher: aau.2011.

Anonymous, “Uncover gems of information”. SAS Institute. Retrieved from the World Wide Web on January 28, 2002. http://www.sas.com/products/miner/index.html

KDnuggets . Polls,” Data Mining Methodology “, analytics Summit, Aug 2007.

Peter A. Flach Nicolas Lachiche, “Confirmation-Guided Discovery of First-Order Rules with Tertius”, Machine Learning, 2001.

E.M. Knorr and R.T. Ng. “A unified notion of outliers: Properties and computation”. In Proc. KDD 1997, pages 219–222, 1997.

Trybula, Walter J. “Data Mining and Knowledge Discovery” Annual review of Information Science and Technology (ARIST); (32): 197 – 229, 1997.


Refbacks

  • There are currently no refbacks.


 
 
  
 

 

  


About ASRJETS | Privacy PolicyTerms & Conditions | Contact Us | DisclaimerFAQs 

ASRJETS is published by (GSSRR).