eprintid: 4276
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/42/76
datestamp: 2023-11-09 16:15:57
lastmod: 2023-11-09 16:15:57
status_changed: 2023-11-09 15:58:04
type: conference_item
metadata_visibility: show
creators_name: Fageeri, S.O.
creators_name: Ahmad, R.
creators_name: Baharudin, B.B.
title: A semi-apriori algorithm for discovering the frequent itemsets
ispublished: pub
keywords: Association rules; Iterative methods; Learning algorithms; Supports, Apriori algorithms; Apriori techniques; Confidence; Frequent itemset; Iterative strategy; Mining algorithms; Research challenges; Traditional approaches, Data mining
note: cited By 1; Conference of 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 ; Conference Date: 3 June 2014 Through 5 June 2014; Conference Code:112912
abstract: Mining the frequent itemsets are still one of the data mining research challenges. Frequent itemsets generation produce extremely large numbers of generated itemsets that make the algorithms inefficient. The reason is that the most traditional approaches adopt an iterative strategy to discover the itemsets, that's require very large process. Furthermore, the present mining algorithms cannot perform efficiently due to high and repeatedly database scan. In this paper we introduce a new binary-based Semi-Apriori technique that efficiently discovers the frequent itemsets. Extensive experiments had been carried out using the new technique, compared to the existing Apriori algorithms, a tentative result reveal that our technique outperforms Apriori algorithm in terms of execution time. © 2014 IEEE.
date: 2014
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938765772&doi=10.1109%2fICCOINS.2014.6868358&partnerID=40&md5=43d9806c0645660332a405f83c3f4dc0
id_number: 10.1109/ICCOINS.2014.6868358
full_text_status: none
publication: 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 - Proceedings
refereed: TRUE
isbn: 9781479943913
citation:   Fageeri, S.O. and Ahmad, R. and Baharudin, B.B.  (2014) A semi-apriori algorithm for discovering the frequent itemsets.  In: UNSPECIFIED.