Association Rule in Recommendation to Reduce Scalability and Sparsity

In this Era of Internet, each and every people uses online websites for getting things done. Before purchasing any product users check the feedback /review related to that product on internet. Some system use information retrieval technique, so they will find the user tests and recommend the product to users.There are various recommendation technique are available. We proposed recommendation system for bike with the help of collaborative filtering technique. In which we are considering technical parameters for making dataset. Finding recommendation value Extract the parameters with thresholdvalue. Also use text comments and apply association rules for finding recommendation bike in market.It gives better result by overcome scalability and sparsity problem.