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Application of Incremental Mining and Apriori Algorithm on Library Transactional Database

by Gunjan Mehta, Deepa Sharma, Ekta Chauhan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 73 - Number 8
Year of Publication: 2013
Authors: Gunjan Mehta, Deepa Sharma, Ekta Chauhan
10.5120/12760-9336

Gunjan Mehta, Deepa Sharma, Ekta Chauhan . Application of Incremental Mining and Apriori Algorithm on Library Transactional Database. International Journal of Computer Applications. 73, 8 ( July 2013), 12-18. DOI=10.5120/12760-9336

@article{ 10.5120/12760-9336,
author = { Gunjan Mehta, Deepa Sharma, Ekta Chauhan },
title = { Application of Incremental Mining and Apriori Algorithm on Library Transactional Database },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 73 },
number = { 8 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume73/number8/12760-9336/ },
doi = { 10.5120/12760-9336 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:40:04.865231+05:30
%A Gunjan Mehta
%A Deepa Sharma
%A Ekta Chauhan
%T Application of Incremental Mining and Apriori Algorithm on Library Transactional Database
%J International Journal of Computer Applications
%@ 0975-8887
%V 73
%N 8
%P 12-18
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is used to extract hidden, predictive information from large databases, which can be used for predicting future trends and allowing businesses to make knowledge- driven decisions [1]. In this paper we explain how Apriori algorithm can be applied on the university's library transactional database in order to find out the frequent book items and generate rules on these book items so as to predict the book borrowing behavior of the students. It then explains how incremental mining when incorporated by adding five more transactions to the original set of ten transactions changes the number of frequent item-sets and association rules generated by the algorithm.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Apriori algorithm associations rule mining incremental data mining

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