A Novel approach to Crowd sourced Websites Question Answering for Medical Knowledge

Authors(2) :-Chintalapati Chandiprasad, M. Jayaram

A standout amongst the most vital difficulties of removing information from the restorative group sourced Q&A sites is that the nature of question-answer sets isn't ensured. The inquiries asked by patients can be boisterous and equivocal. The appropriate responses' quality shifts because of reasons, for example, specialists' mastery, their level of responsibility, and their motivation of noting questions. To extricate valuable learning, it is critical to recognize significant and adjust data from disconnected or off base data. In this paper, we built up a proposed conspire Opinion Target Finding (OPF) that can consequently give superb learning triples separated from the boisterous inquiry answer sets, and in the meantime, evaluate aptitude for the specialists who give replies on these Q&A sites. The Medical Knowledge Extraction (MKE) framework is based upon a reality revelation structure, where we mutually assess dependability of answers and specialist aptitude from the information with no supervision.

Authors and Affiliations

Chintalapati Chandiprasad
M.Tech Scho1lar, Department of CSE, Universal College of Engineering & Technology, Dokkiparru, Guntur, Andhra Pradesh, India
M. Jayaram
Associate Professor, Department of CSE, Universal College of Engineering & Technology, Dokkiparru, Guntur, Andhra Pradesh, India

Question & Answering, Opinion Target Finding, Medical Knowledge Extraction, Medical Crowd.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 880-884
Manuscript Number : CSEIT1831259
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Chintalapati Chandiprasad, M. Jayaram, "A Novel approach to Crowd sourced Websites Question Answering for Medical Knowledge", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.880-884, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831259

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