A Smart Media-Based Recommendation System
Smart media devices such as: smartphones and tablets are getting more powerful, smarter, cheaper and hence more popular. Recommendation systems become very common in e-business and e-Commerce, for example: Amazon, Google, eBay, Facebook, etc. all are using recommendation systems to promote their business. Recommendation systems are rarely used in learning; however it can be very useful. The proposed project works as follow: Send a learning query to sites, sources and repositories across the Web and gather relevant information through the use of recommendation system that filter all the useless or irrelevant materials off the main list of recommended items. Filter result from other user’s preference using collaborative-filtering, having the current query in mind. Use TFIDF for content-based filtering and ranking of the shortlisted pages or articles. Present the shortlist based on their rank to the user of the system.