Now a days, Recommendations system is a pillar for each web portal and application. Recommendation systems are not specific to a single domain, it is applicable in diverse domains. It is used in social networking sites for posts and recommending friends; or e-commercial websites for giving suggestions for the user about products and services; or it’s a movie recommendations based on the user’s interest and suggest the upcoming movies which is well suited for a respective user. At the backend, the machine learning is used to give better recommendations and suggestions. In the paper, various algorithms are discusses with their implementation areas. A comparative study is discussed in the paper and a proposed algorithm which is well suited for the web blogs and the microblogs websites. A proposed approach uses the machine learning methodologies based on the user’s point of interest. User’s hobbies and the likings are the major concerns when the recommendation system recommends the posts and friends. Proposed algorithm is derived from various aspects to call it a hybrid algorithm for recommendation systems.

Index Terms- Content Curation, Hybrid Computing, Machine Learning, Recommendations Systems, Web Blogs