Output details
11 - Computer Science and Informatics
Liverpool Hope University
Article title
A sliding windows based dual support framework for discovering emerging trends from temporal data
Type
D - Journal article
Title of journal
Knowledge-Based Systems
Article number
-
Volume number
23
Issue number
4
First page of article
316
ISSN of journal
09507051
Year of publication
2010
URL
-
Number of additional authors
-
Additional information
<15> A novel Dual Support Apriori for Temporal data (DSAT) algorithm is developed for discovering Jumping Emerging Patterns (JEPs) from time series data using a sliding window technique.
This is particularly effective when performing trend analysis on data that have elements that vary over time. Our framework is different from the previous work on JEP in that we do not rely on item sets borders with a constrained search space.
This work contributed toward successful PhD work performed by S. Khan (jointly supervised by Dr Reid and Dr Tawfik at Liverpool Hope University along with Dr Coenen at Liverpool University).
Interdisciplinary
-
Cross-referral requested
-
Research group
1 - Centre for Applicable Mathematics and Systems Science (CAMSS)
Citation count
4
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
