Economics at your fingertips  

Normal Distribution Based Similarity Profiled Temporal Association Pattern Mining (N-SPAMINE)

Vangipuram Radhakrishna (), P.V.kumar () and V.janaki ()
Additional contact information
Vangipuram Radhakrishna: VNR Vignana Jyothi Institute of Engineering and Technology, India
P.V.kumar: University College of Engineering, Osmania University, India
V.janaki: Vaagdevi Engineering College, India

Database Systems Journal, 2017, vol. 7, issue 3, 22-33

Abstract: Temporal patterns in time stamped temporal databases are sequences of support values and hence, they are represented as vectors. This makes it challenging to obtain similar association patterns in context of time stamped temporal databases whose support trends change similar to a reference support sequence trend. The main idea of this work is to study the possibility of applying normal distribution concept to find similarly varying temporal patterns. This paper introduces a new approach, called N-SPAMINE for mining similarity profiled temporal association patterns by applying normal distribution which is first of its kind of approach for finding similar association patterns and uses the novel dissimilarity measure for obtaining dissimilarity between chosen temporal pattern and the reference. The results show that the proposed approach is correct and complete.

Date: 2017
References: View complete reference list from CitEc
Citations Track citations by RSS feed

Downloads: (external link) (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Access Statistics for this article

Database Systems Journal is currently edited by Ion Lungu

More articles in Database Systems Journal from Academy of Economic Studies - Bucharest, Romania Contact information at EDIRC.
Series data maintained by Adela Bara ().

Page updated 2017-09-29
Handle: RePEc:aes:dbjour:v:7:y:2017:i:3:p:22-33