Bitwise dynamic itemset counting algorithm

Preetham Kumar, Preetika Bhatt, Raka Choudhury

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Data mining has gained a lot of importance as well as popularity in today's world. Data mining provides a systematic approach for gathering useful information from huge amounts of data. Many algorithms are being written for this purpose. One of them is Dynamic Itemset Counting Algorithm. Only if all the subsets are frequent, an itemset is considered frequent in this algorithm. As the itemsets are counted, they are grouped together into four separate categories namely, dashed circle, dashed box, solid circle, and solid box. Here, a variation of this existing algorithm is being provided. Bitwise Dynamic Itemset Counting Algorithm aims to modify the existing algorithm such that its time complexity reduces. In today's world, it is very important not only to collect information from raw data but also to do it fast. Time required for running any algorithm on a collection of data directly impacts the usefulness of that algorithm. Hence, reduction of the time complexity of an existing data mining algorithm such as Dynamic Itemset Counting Algorithm shall be useful. In the existing algorithm, all transactions are checked during every pass for detecting the frequency of the different itemsets. The modified algorithm attempts to suggest a more efficient way to achieve the same results. It also aims at reducing the number of comparisons and the required number of scans. Bitwise Dynamic Itemset Counting Algorithm uses bitwise mapping of all transactions corresponding to each distinct item and the possibility check.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479978489
DOIs
Publication statusPublished - 17-03-2016
Event6th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015 - Madurai, India
Duration: 10-12-201512-12-2015

Conference

Conference6th IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015
CountryIndia
CityMadurai
Period10-12-1512-12-15

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

Cite this

Kumar, P., Bhatt, P., & Choudhury, R. (2016). Bitwise dynamic itemset counting algorithm. In 2015 IEEE International Conference on Computational Intelligence and Computing Research, ICCIC 2015 [7435752] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCIC.2015.7435752