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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, 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: | 000337068 |
| 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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