Forecasting Supplies Inventory Using Sequential Pattern Analysis
Pages 291 - 294
Abstract
One of the fundamental data mining tasks was discovering unexpected and useful patterns in databases. The most popular data mining is sequential pattern mining. Analyzing sequential pattern has been applied in much real-life business such retailing, customer buying behavior, inventory management, and financial industries, This paper used sequential pattern analysis in the supplies inventory management of a university. The goal is to identify what particular items need to have more stocks and determine when they will need it and to predict the request pattern of items of every department. This paper also defined and reviewed the task of sequential pattern mining and its applications are. Moreover, Apriori Algorithm, a known effective computing solution for small datasets was used and integrated to the current supplies inventory management system of the university to produce a sequential pattern on itemsets being requested by different departments. Lastly, this research presented and analyzed the results of the implemented sequential pattern mining algorithm and gave some recommendations.
References
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Burja, C., & Burja, V. (2010). Analysis Model For Inventory Management. Retrieved from https://www.upet.ro/annals/economics/pdf/2010/20100104.pdf
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Index Terms
- Forecasting Supplies Inventory Using Sequential Pattern Analysis
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Published In
December 2018
344 pages
ISBN:9781450366298
DOI:10.1145/3301551
Copyright © 2018 ACM.
© 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.
In-Cooperation
- The Hong Kong Polytechnic: The Hong Kong Polytechnic University
- TU: Tianjin University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 29 December 2018
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