Mining Time Series Data using Optimized Apriori Algorithm |
Author(s): |
| Akshay Malapure , Pdea's College of Engineering Manjari; Rajashri Kalbhor, Pdea's College of Engineering Manjari; Anupama Patil, Pdea's College of Engineering Manjari; Aditi Pawar, Pdea's College of Engineering Manjari |
Keywords: |
| Association Rule Mining, Apriori Algorithm, Apriori Tid Algorithm, Time Series |
Abstract |
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A Time series is a collection of observation made sequentially in time. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Mining association rule is one of the common forms in data mining, in which the critical problem is to gain the frequent item-sets efficiently. In this project we are using two algorithms. Through Apriori and optimized Apriori algorithms frequent item sets are generated which would be used for analysis of data .Real time transactional data is being used on which rules generated through algorithm are applied in order to get statistics of products sold. This project reduces a lot of time required to generate results so as to increase sales, product etc. In the end result generated through both algorithms are analyzed. |
Other Details |
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Paper ID: IJSRDV6I30493 Published in: Volume : 6, Issue : 3 Publication Date: 01/06/2018 Page(s): 1395-1397 |
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