Mining food industry's multidimensional data to produce association rules using apriori algorithm as a basis of business strategy
Abstract:The
food industry sell a range of product variations. The company want to
take advantage to build business strategy from huge information which is
stored in data warehouse. In this case, data mining technology needs to
be implemented to explore valuable information on transactional data to
assess customer's preferences for products sold as a business strategy.
Date of Conference:
20-22 March 2013
Date Added to IEEE Xplore:
05 August 2013
ISBN Information:
INSPEC Accession Number:
13697620
Publisher:
IEEE
IEEE Keywords Association rules, Food products, Business, Flowcharts, Communications technology, Correlation
Author Keywords Three Validation Levels, Data Reduction, Apriori, Support, Confidence, Association Rules
IEEE Keywords Association rules, Food products, Business, Flowcharts, Communications technology, Correlation
Author Keywords Three Validation Levels, Data Reduction, Apriori, Support, Confidence, Association Rules
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Cited:
F. Sulianta, T. H. Liong and I. Atastina, "Mining food industry's multidimensional data to produce association rules using apriori algorithm as a basis of business strategy," 2013 International Conference of Information and Communication Technology (ICoICT), Bandung, 2013, pp. 176-181, doi: 10.1109/ICoICT.2013.6574569. keywords: {Association rules;Food products;Business;Flowcharts;Communications technology;Correlation;Data Reduction;Apriori;Support;Confidence;Association Rules;Three Validation Levels},
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