Mining Frequent Itemsets from Online Data Streams: Comparative Study
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 7
Abstract
Online mining of data streams poses many new challenges more than mining static databases. In addition to the one-scan nature, the unbounded memory requirement, the high data arrival rate of data streams and the combinatorial explosion of itemsets exacerbate the mining task. The high complexity of the frequent itemsets mining problem hinders the application of the stream mining techniques. In this review, we present a comparative study among almost all, as we are acquainted, the algorithms for mining frequent itemsets from online data streams. All those techniques immolate with the accuracy of the results due to the relatively limited storage, leading, at all times, to approximated results.
Authors and Affiliations
HebaTallah Nabil, Ahmed Eldin, Mohamed Belal
Keywords
Related Articles
- EP ID EP93421
- DOI 10.14569/IJACSA.2013.040717
- Views 100
- Downloads 0
A Congestion Avoidance Approach in Jumbo Frame-enabled IP Network
Jumbo frame is as an approach that allows for higher utilization of larger packet sizes on a domain-wise basis, decreasing the number of packets processed by core routers while not having any adverse impact on the...
Assessment Model for Language Learners’ Writing Practice (in Preparing for TOEFL iBT) Based on Comparing Structure, Vocabulary, and Identifying Discrepant Essays
This study aims to investigate if learners of English can improve computer-assisted writing skills through the analysis of the data from the post test. In this study, the focus was given to intermediate-level students of...
SLA for E-Learning System Based on Cloud Computing
The Service Level Agreement (SLA) becomes an important issue especially over the Cloud Computing and online services that based on the ‘pay-as-you-use’ fashion. Establishing the Service level agreements (SLAs), which can...
Detection of Malware and Malicious Executables Using E-Birch Algorithm
Malware detection is one of the challenges to the modern computing world. Web mining is the subset of data mining used to provide solutions for complex problems. Web intelligence is the new hope for the field of computer...
Brainwaves for User Verification using Two Separate Sets of Features based on DCT and Wavelet
This paper discusses the effectiveness of brain waves for user verification using electroencephalogram (EEG) recordings of one channel belong to single task. The feature sets were previously introduced as features for EE...