期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2015
卷号：4
期号：5
页码：2163-2170
出版社：Shri Pannalal Research Institute of Technolgy
摘要：Nowadays various Pharmaceuticals industries are using the Social media in which industries may include sick persons, Doctors, Pharmaceuticals companies etc. There exists a lot of medical sites and conference blogs which are the part of sentimental analysis. These are used in many applications such as text based information (i.e., social media such as twitter, Facebook ), market intelligence, drug observations ,taking the opinions about heath related information and also to detect the impact of Adverse Drug Reaction(ADR) automatically by making use of Pharmacovigilance techniques. By using the already existing tools which are used to examine the health related information and sentimental analysis we are not able to get the sufficient classification accuracies. And also they are not able to extract the exploratory and transferable features; hence they are lacking the biased features. In our design we use the Advanced NLP approaches to generate the functional features from the input and using the advanced machine learning algorithms to achieve the classification accuracies. Here we rely on text classification approach that generates huge set of features which represents many semantic properties like sentiment, polarity, topics which are useful to manifest the experience of the user when they talk about ADR. We present two datasets that are prepared by user to perform the job of ADR detection from the data posted by the user on internet. We also verify whether the combining training data which have been taken from different collections can improve the automatic classification accuracies and address the issue of data imbalance. This is very useful where there exists a large datasets and also reduces time and cost of those data.
