Improving Ecommerce Performance by Dynamically Predicting the Purchased Items Using FUP Incremental Algorithm-Reference-Cited by-同舟云学术

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Improving Ecommerce Performance by Dynamically Predicting the Purchased Items Using FUP Incremental Algorithm

Published:2022-07-06 Issue: Volume: Page:137-147
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
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Author:

Kalaiselvi K.,Deepa Thilak K.,Saranya S.,Rajeshkumar T.,Malathi M.,Vijay Anand M.,Kumaresan K.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-9967-2_14

Reference8 articles.

1. Frequent Itemset Mining Dataset Repository, http://fimi.ua.ac.be/data (2004)

2. Apache Hadoop, http://hadoop.apache.org/ (2013)

3. Apache Mahout, http://mahout.apache.org/ (2013)

4. R. Agrawal, J. Shafer, Parallel mining of association rules. IEEE Trans. Knowl. Data Eng., pp. 962–969 (1996)

5. R. Agrawal, R. Srikant, Fast algorithms for mining association rules in large databases, in Proceedings of VLDB, pp. 487–499 (1994)

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