Health Adviser: Social Question and Answer System u sing Datamining
Satish Kumar.T1, Vishwakiran2, Preran Devaiah3 

1Satish Kumar.T, Computer Science and Engineering, BMSIT&M, Bangalore, India.
2Vishwakiran, Computer Science and Engineering, BMSIT&M, Bangalore, India.
3Preran Devaiah, Research Scholar, Computer Science and Engineering, BMSIT&M, Bangalore, India. 

Manuscript received on 03 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 4294-4297 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2802078219/19©BEIESP | DOI: 10.35940/ijrte.B2802.078219
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Abstract: Question and answer systems play a crucial role in providing answers to users that seek it, primarily in the case of non-factual questions. A Social Q&A system aims to integrate properties of social networks like similar interests of the users and mutual trust between within a set of friends which makes the reliability of certain answers more prudent. In simple terms, it aims to find a expert that can provide the right answers, ideally within the user’s social circle. Our project endeavors to serve pregnant mothers in answering their private or non-private questions regarding their pregnancies. Our system provides a platform for the to-be mothers to ask their questions to experts who can suggest suitable advises for their benefit. The user also has the added advantage of accessing information from experts who belong to their social circle thereby reducing the anonymity of the expert. We have compared the accuracy of few machine learning algorithms that includes Decision Tree (DT), Support Vector Machine (SVM), K-Nearest Neighbor kNN), Logistic Regression (LR), ZeroR (the baseline classifier). Our model has an accuracy of over 75%, while demonstrating robustness across learning algorithms.
Index Terms: Decision Tree, Data Mining, Health Adviser, Social Q&A System.

Scope of the Article: Health Monitoring and Life Prediction of Structures