IIUM Repository

Frequent itemset mining in high dimensional data: a review

Md. Zaki, Fatimah Audah and Zulkurnain, Nurul Fariza (2019) Frequent itemset mining in high dimensional data: a review. In: 5th International Conference on Computational Science and Technology (ICCST 2018), 29th-30th August 2018, Kota Kinabalu, Sabah.

[img] PDF - Published Version
Restricted to Registered users only

Download (698kB) | Request a copy
PDF (SCOPUS) - Supplemental Material
Download (186kB) | Preview


This paper provides a brief overview of the techniques used in frequent itemset mining. It discusses the search strategies used; i.e. depth first vs. breadth-first, and dataset representation; i.e. horizontal vs. vertical representation. In addition, it reviews many techniques used in several algorithms that make frequent itemset mining more efficient. These algorithms are discussed based on the proposed search strategies which include row-enumeration vs. column-enumeration, bottom-up vs. top-down traversal, and a number of new data structures. Finally, the paper reviews on the latest algorithms of colossal frequent itemset/pattern which currently is the most relevant to mining highdimensional dataset.

Item Type: Conference or Workshop Item (Plenary Papers)
Additional Information: 4123/67014
Uncontrolled Keywords: Data mining, High-dimensional data
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering
Depositing User: DR Nurul Fariza Zulkurnain
Date Deposited: 05 Mar 2019 12:07
Last Modified: 25 Nov 2019 12:23
URI: http://irep.iium.edu.my/id/eprint/67014

Actions (login required)

View Item View Item


Downloads per month over past year