A framework for cloud based hybrid recommender system for big data mining

Abstract

The modern web platforms dealing with large number of items are using recommender systems to suggest automatically new interesting items to users and, hence, to keep them using the platform. From the users’ perspective, recommender systems help them to handle information. In this paper, a Framework for Cloud Based Hybrid Recommender System (FCHRS) for Big Data Mining is proposed and methods and algorithms that are used in the framework are discussed. It is based on the Iterative collaborative filtering, which traditionally is the most used approach, and on the Sentiment Analysis (known as opinion mining) as well. It refers to the use of natural language processing, text analysis and computational linguisticsto identify and to extract subjective information from source materials. Thus it becomes essential for the enterprise to mine social media data (big data) to make recommendations. The combination of results of two algorithms provides more useful business intelligence. This combination is new and unexplored area of research.