Cloud API for gradual patterns

Cloud API framework for crossing IoT data streams and extracting gradual patterns
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Updated 12 Apr 2022

Integrating gradual pattern mining tools into the Cloud

A Docker implementation of OGC/SensorThings API with gradual pattern mining tools integrated into it

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Research paper is available via this link:

  • Owuor, Dickson, Anne Laurent, Joseph Orero, and Olivier Lobry. "Gradual Pattern Mining Tool on Cloud." Extraction et Gestion des Connaissances: Actes EGC'2021 (2021).

Requirements

You will be required to install Docker

Installation

  1. Download package

  2. Use a command line program with the local package:

$docker-compose up

Usage

Launch your Browser and go to: http://localhost:8080

NB: a sample IoT data set provided in sample_data, follow the steps to populate your database

References

  • Owuor D.O., Laurent A., Orero J.O. (2020) Exploiting IoT Data Crossings for Gradual Pattern Mining Through Parallel Processing. In: Bellatreche L. et al. (eds) ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium. TPDL 2020, ADBIS 2020. Communications in Computer and Information Science, vol 1260. Springer, Cham. https://doi.org/10.1007/978-3-030-55814-7_9

  • Dickson Owuor, Anne Laurent, and Joseph Orero (2019). Mining Fuzzy-temporal Gradual Patterns. In the proceedings of the 2019 IEEE International Conference on Fuzzy Systems (FuzzIEEE). IEEE. https://doi.org/10.1109/FUZZ-IEEE.2019.8858883

Cite As

Dickson Owuor (2024). Cloud API for gradual patterns (https://github.com/owuordickson/cloud-api/releases/tag/v1.0.0), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2022a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired by: Ant Colony Optimization for Gradual Patterns

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Version Published Release Notes
1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.