Information Retrieval Mechanism for Dynamic Health Care

Authors

  • Devi CD PG & Research Dept. of Computer Applications, Sacred Heart College, Tirupattur, Vellore District, Tamil Nadu, INDIA
  • Thaddeus S Don Bosco College, Yelagiri Hills,Vellore District, Tamil Nadu, INDIA

DOI:

https://doi.org/10.26438/ijcse/v6i9.105107

Keywords:

MongoDB, Ontology

Abstract

In spite of the commendable success of Big Data, there are still many challenges with regard to storage, retrieval, analysis and prediction. A framework was proposed for information retrieval by integrating ontology models with Big Data. Evaluation of this framework with different domain models is a invariable work to validate this model. This study applies the framework to health care data and thus identifies the strengths and weaknesses of the framework.

References

[1] Fr. Thaddeus, C. DharmaDevi, S. Deepa, “A Framework for ontology-driven big data applications”, IJAER, Vol.10 (No.79), ISSN 0973-4562, 2015.

[2] Karl Seguin, “The Little MongoDB for 2.6”.

[3] Chieh Ming Wu, “Comparisons between MongoDB and MS-SQL Databases on the TWC Website”.

[4] Natalya F.Noy and Deborah L. McGuinness, “Ontology Development”.

[5] Fr. Thaddeus, C. DharmaDevi, “Ontology Bridge for Information Retrieval”, in the Proceedings of International Conference on Computing Paradigms, 2016.

[6] Furkh Zeshan and Radziah Mohamada, “Medical Ontology in the Dynamic Healthcare Environment”, in Elsevier Ltd, 1877-0508, 2012.

[7] Sreekanth R, Golajapu Venu Madhava Rao, Srinivas Nanduri, “Big Data Electronic Health Records Data Management and Analysis on Cloud with MongoDB: A NoSQL Database”, in IJAGT, 2309-4893, 2015.

[8] Manju K.K, Srinitya G, “Analysis and Prognosis of Cancer with Big Data Analytics”, in IJRASET, 2321-9653, 2016.

Downloads

Published

2018-09-30
CITATION
DOI: 10.26438/ijcse/v6i9.105107
Published: 2018-09-30

How to Cite

[1]
C. D. Devi and S. Thaddeus, “Information Retrieval Mechanism for Dynamic Health Care”, Int. J. Comp. Sci. Eng., vol. 6, no. 9, pp. 105–107, Sep. 2018.

Issue

Section

Research Article