Predicting the Buying Behaviour Pattern of Grocery Items by Women Consumers: An Empirical Study of Thanjavur

Authors

  •   Kavitha Venkatachari Associate Dean, IBS, Mumbai

Keywords:

Super Market, Data Mining, Association Rule, Buying Behaviour, Apriori and Eclat Algorithm, Pattern.

Abstract

Apriori algorithm is one of the major algorithm used in mining to find frequent item sets in a large transactional data. Companies ranging from small scale to large scale all data is stored in various forms which keeps on growing. If the data is distributed all over the places in a vertically fragmented way then it is very difficult to combine the data and store it in a central location. From the data base entry we can understand that some items are repeatedly entered and they are having the common associations between them.

From this study we can understand that apriori algorithm is the best algorithm and it takes less execution time and it gives the strong association rules. By this association rule we can get the relationships between one item and several important attributes. From the visualization tools to show the results helping to give decision proposals of the grocery item.

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Published

2019-12-31

How to Cite

Venkatachari, K. (2019). Predicting the Buying Behaviour Pattern of Grocery Items by Women Consumers: An Empirical Study of Thanjavur. SFIMAR Research Review, 14(2), 50–57. Retrieved from https://sfimar.srels.org/index.php/srr/article/view/156124

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Articles

References

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