Sentiment Analysis(SA) can be a natural language processing(NLP) task that extracts opinions from the given text and classifies them as a negative or positive. Research works in SA is mostly conducted in English. Nowadays, the web indexes and other websites related to reviews also support non-English languages. It is therefore necessary to perform SA for these languages as well. There are numerous works found in the literature for SA in other languages worldwide. However, SA for Indian languages needs exploration. In this paper, we discuss various available lexicon resources and often used SA techniques in some Indian languages. Moreover, we present the theoretical parametric evaluation of our studied techniques and we also discuss challenges, which were identified during SA in Indian Languages.
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL
₹10000 (INR)
2019