IADIS International Journal on Computer Science and Information Systems

Published by IADIS (International Association for Development of the Information Society) • ISSN (Online): 1646-3692 • ISSN (Print): 1646-3692
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Design and Analysis of Similarity Measure for Discovering Similarity Profiled Temporal Association Patterns

Vangipuram Radhakrishna *
P. V. Kumar *
V. Janaki *
* 1Department of Information Technology, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India -500096 2Retd. Professor, Computer Science and Engg Department, University College of Engineering, Osmania University, Hyderabad, India 3Computer Science and Engg Department, Vaagdevi College of Engineering, Warangal, India (Portugal)
* 1Department of Information Technology, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India -500096 2Retd. Professor, Computer Science and Engg Department, University College of Engineering, Osmania University, Hyderabad, India 3Computer Science and Engg Department, Vaagdevi College of Engineering, Warangal, India (Portugal)
* 1Department of Information Technology, VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India -500096 2Retd. Professor, Computer Science and Engg Department, University College of Engineering, Osmania University, Hyderabad, India 3Computer Science and Engg Department, Vaagdevi College of Engineering, Warangal, India (Portugal)

Abstract

A wide variety of real time applications generate temporal data. Determining and unearthing similar temporal association patterns is complex and challenging task when considering time stamped temporal databases. Previous works have considered only existin g distance measure and did not address retrieval and discovery of similar temporal association patterns using new distance measures. In this paper, we design a new similarity measure which suits the temporal context that can be applied to obtain all valid STAP (similar temporal association patterns). Our approach considers approximating the association pattern support bounds and applying the proposed similarity measure. The results show the proposed approach has better computational complexity compared to o ther approaches and improve d time efficiency.

Keywords

Distance Function Temporal Pattern Similarity Degree Association Rules Support Sequence
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Funding: This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest: The authors declare no competing financial or institutional interests.
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License: Creative Commons Attribution 4.0 International (CC BY 4.0).
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Radhakrishna, et al. (2017). Design and Analysis of Similarity Measure for Discovering Similarity Profiled Temporal Association Patterns. IADIS International Journal on Computer Science and Information Systems, 12(1). https://doi.org/10.33965/ijcsis_2017_v12i1_05
Radhakrishna, et al. "Design and Analysis of Similarity Measure for Discovering Similarity Profiled Temporal Association Patterns." IADIS International Journal on Computer Science and Information Systems, vol. 12, no. 1, 2017. https://doi.org/10.33965/ijcsis_2017_v12i1_05
Radhakrishna, et al. "Design and Analysis of Similarity Measure for Discovering Similarity Profiled Temporal Association Patterns." IADIS International Journal on Computer Science and Information Systems 12, no. 1 (2017). https://doi.org/10.33965/ijcsis_2017_v12i1_05