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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Issue: June 2022

Volume 7 | Issue 6

Impact factor: 8.15

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Paper Title: DRUG RECOMMENDATION TECHNIQUES BASED ON ASPECT LEVEL REVIEWS USING MACHINE LEARNING ALGORITHMS
Authors Name: Dr. K. Jayasakthi velmurugan , Elakkiya J
Unique Id: IJSDR2201001
Published In: Volume 7 Issue 1, January-2022
Abstract: Drugs plays a major role in our day-to-day life. Analysis of the drugs is an important task. Aspect-level review is the process of associating the various opinions with the specific sentiments by customer reviews. Semi-supervised clustering is used to train the initial model which is of labelled data and then later it is used for unlabelled data. Additionally, the presence of some drug properties, such as side effects and effectiveness, depends on characteristics of patients, such as age, gender, lifestyles, and genetic profiles. The goal is to provide a system to assist medical professionals and drug consumers in choosing and finding drugs that suit their needs. This paper develops an approach that allows querying for drugs that satisfy a set of conditions. And also recommend the drugs based on user reviews. These reviews are collected from multiple user’s feedbacks and implement sentiment analysis approach to predict the positive feedback about drugs and provide priority of user searched query. The proposed paper represents the working process of Medicine information, pre-processing and clustering of data on aspect-based sentiment analysis done using machine learning techniques.
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Cite Article: "DRUG RECOMMENDATION TECHNIQUES BASED ON ASPECT LEVEL REVIEWS USING MACHINE LEARNING ALGORITHMS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 1, page no.1 - 8, January-2022, Available :http://www.ijsdr.org/papers/IJSDR2201001.pdf
Downloads: 00096793
Publication Details: Published Paper ID: IJSDR2201001
Registration ID:193803
Published In: Volume 7 Issue 1, January-2022
DOI (Digital Object Identifier):
Page No: 1 - 8
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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