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International Symposium on Distributed Computing and Artificial Intelligence

DCAI 2018: Distributed Computing and Artificial Intelligence, 15th International Conference pp 164–171Cite as

A Web-Based Micro-service Architecture for Comparing Parallel Implementations of Dissimilarity Measures

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 800))

Abstract

The performance of an application can be significantly improved by using parallelization, as well as by defining micro-services which allow the distribution of the work into several independent tasks. In this paper, we show how a micro-service architecture can be used for developing an efficient and flexible application for the nearest neighbor classification problem. Several dissimilarity measures are compared, in terms of both accuracy and computational time, for sequential as well parallel executions. In addition, a web-based interface was developed in order to facilitate the interaction with the user and easily monitoring the progress of the experiments.

A.-L. Uribe-Hurtado—Estudiante del Doctorado en Ingeniería, Industria y Organizaciones - Universidad Nacional de Colombia - Sede Manizales.

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Notes

  1. 1.

    Available at: http://www.37steps.com/prhtml/prdisdata/specdata.html.

  2. 2.

    http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.distance_metrics.html and https://docs.scipy.org/doc/scipy/reference/spatial.distance.html.

  3. 3.

    https://docs.docker.com/engine/docker-overview/#docker-registries.

References

  1. Ciavotta, M., Alge, M., Menato, S., Rovere, D., Pedrazzoli, P.: A microservice-based middleware for the digital factory. Procedia Manufact. 11, 931 – 938 (2017). 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2017, 27-30 June 2017, Modena, Italy (2017)

    Google Scholar 

  2. Cui, M., Cui, J., Li, H.: Dimensionality reduction for histogram features: a distance-adaptive approach. Neurocomputing 173, 181–195 (2016)

    Article  Google Scholar 

  3. Duin, R.P.W., Juszczak, P., de Ridder, D., Paclik, P., Pekalska, E., Tax, D.M.J.: PRTools4: a matlab toolbox for pattern recognition (2007)

    Google Scholar 

  4. Florindo, J.B., Bruno, O.M.: Texture classification using non-euclidean Minkowski dilation. Phys. A 493, 189–202 (2018)

    Article  MathSciNet  Google Scholar 

  5. Flynn, M.J.: Some computer organizations and their effectiveness. IEEE Trans. Comput. C-21, 948–960 (1972)

    Article  Google Scholar 

  6. Gutiérrez, P.D., Lastra, M., Bacardit, J., Benítez, J.M., Herrera, F.: GPU-SME-kNN: scalable and memory efficient kNN and lazy learning using GPUs. Inf. Sci. 373, 165–182 (2016)

    Article  Google Scholar 

  7. Jain, A.K., Duin, R.P.W.: Pattern recognition. In: Gregory, R.L. (ed.) The Oxford Companion to the Mind, 2 edn., pp. 698–703. Oxford University Press, Oxford (2004)

    Google Scholar 

  8. Santana, F., Santiago, R.: A generalized distance based on a generalized triangle inequality. Inf. Sci. 345, 106–115 (2016)

    Article  MathSciNet  Google Scholar 

  9. Swaminathan, M., Yadav, P.K., Piloto, O., Sjöblom, T., Cheong, I.: A new distance measure for non-identical data with application to image classification. Pattern Recogn. 63, 384–396 (2017)

    Article  Google Scholar 

  10. Todeschini, R., Ballabio, D., Consonni, V., Grisoni, F.: A new concept of higher-order similarity and the role of distance/similarity measures in local classification methods. Chemometr. Intell. Lab. Syst. 157, 50–57 (2016)

    Article  Google Scholar 

  11. Wong, T.T.: Performance evaluation of classification algorithms by k-fold and leave-one-out cross validation. Pattern Recogn. 48(9), 2839–2846 (2015)

    Article  Google Scholar 

Download references

Acknowledgments

The authors acknowledge support to attend DCAI’18 provided by Facultad de Administración, Universidad Nacional de Colombia - Sede Manizales (UNAL) and GAIA research group. Anonymous reviewers are acknowledged as well as Oscar David Arbeláez-Echeverri for his support in the development of the application.

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Authors and Affiliations

  1. Facultad de Administración, Departamento de Informática y Computación, Grupo de Ambientes Inteligentes Adaptativos - GAIA, Universidad Nacional de Colombia - Sede Manizales, km 7 vía al Magdalena, Manizales, 170003, Colombia

    Daniel-Stiven Valencia-Hernández, Ana-Lorena Uribe-Hurtado & Mauricio Orozco-Alzate

Authors
  1. Daniel-Stiven Valencia-Hernández
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  2. Ana-Lorena Uribe-Hurtado
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  3. Mauricio Orozco-Alzate
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Corresponding author

Correspondence to Ana-Lorena Uribe-Hurtado .

Editor information

Editors and Affiliations

  1. BISITE Digital Innovation Hub. Edificio Multimedia I+D+i, University of Salamanca, Salamanca, Spain

    Fernando De La Prieta

  2. Faculty of Engineering, Department of Electronics, Information and Communication, Osaka Institute of Technology, Osaka, Osaka, Japan

    Sigeru Omatu

  3. Department of Computing Systems, School of Industrial Engineers at Albacete, University of Castilla-La Mancha, Albacete, Spain

    Antonio Fernández-Caballero

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Valencia-Hernández, DS., Uribe-Hurtado, AL., Orozco-Alzate, M. (2019). A Web-Based Micro-service Architecture for Comparing Parallel Implementations of Dissimilarity Measures. In: De La Prieta, F., Omatu, S., Fernández-Caballero, A. (eds) Distributed Computing and Artificial Intelligence, 15th International Conference. DCAI 2018. Advances in Intelligent Systems and Computing, vol 800. Springer, Cham. https://doi.org/10.1007/978-3-319-94649-8_20

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