A SURVEY ON DRUG REVIEWS USING DATA MINING MODEL
Abhimanyu D. Sangale, P. N. Kalavadekar · 2016
Many user-centred portals and websites are available now a day for sharing information and interaction; some of them are Amazon, Facebook, Twitter and many more. People who are intrested in any product or any service they will not only search official information but also refer user reviews on it. Due to this, online reviews, forums, portals and blogs for different product are developed and used, but how effectively the data is analysed and exploit such huge information is a challenge. Review mining deals with extracting specific information (positive or negative) from large set of text which is written by internet users. Recent state-of-art approach such as frequency based, relation based approaches and supervised learning shows that favourable results could be obtained. It might be because patients of minority group on internet are are intrested in specific illnesses or drug. Insted of taking reviews from other patients, people intently importune opinions from medical professionals. However, in recent studies shows that patients content reviews where useful in many chronic diseases and their drugs. Patients with a certain condition prefer the information shared by another patient with similar condition. The impact on patients health was found positive by online reviews. User can see information on different drugs and also their final resultant rating based on the text reviews. User has options to browse any drug and write review on any drug they have used and based on their content, application decides the review results as positive or negative. Based on the content of the reviews, system will partition the statements and calculate the threshold of the information related to the drug.