Now a days the usage of Internet and online marketing has become very popular. Millions of products and services are available in online marketing that generate huge amount of information. Hence, it's difficult to find the best suitable services or products compatible to the requirement. Customers directly take decision based on reviews or opinions that are written by others based on their experiences. In this competitive world any person can write anything, this raise the number of fake reviews. Various companies are hiring people to write fake positive reviews about their services or products or unfair negative reviews about their competitors' services or products. This process gives wrong input to the new customers who wish to buy such items and hence we need a system to detect such fake reviews and remove them. In this paper we discuss various supervised, unsupervised and semi supervised data mining techniques for fake review detection based on different features.
Machine learning algorithms
• 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