Instant Answering For Health Seekers Using Machine Learning

Authors(4) :-Periyanga. J, Preethi.B, Priya.M, Ramakrishanan

To bridge the vocabulary gap between health seekers and providers is to code the medical records by jointly utilizing local mining and global learning. The emerging community generated health data is more colloquial in terms of inconsistency, complexity and ambiguity is overcome by machine learning process. Machine learning is achieved by using local mining and global learning techniques. Local mining database gets updated by global learning data. Global learning comprises a large collection of medical resources in its backend which helps to retrieve a related resource to the query based on terminology keywords.

Authors and Affiliations

Periyanga. J
Dhanalakshmi College of Engineering, Kancheepuram District, Chennai, Tamilnadu, India
Dhanalakshmi College of Engineering, Kancheepuram District, Chennai, Tamilnadu, India
Dhanalakshmi College of Engineering, Kancheepuram District, Chennai, Tamilnadu, India
Dhanalakshmi College of Engineering, Kancheepuram District, Chennai, Tamilnadu, India

Machine Learning, NLP, Support Vector Machine

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Publication Details

Published in : Volume 1 | Issue 1 | January-Febuary 2015
Date of Publication : 2015-02-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 335-338
Manuscript Number : IJSRSET151174
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Periyanga. J, Preethi.B, Priya.M, Ramakrishanan, " Instant Answering For Health Seekers Using Machine Learning, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 1, pp.335-338, January-Febuary-2015.
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