Abstract: - Now a days, online reviews have gotten one of the indispensable components for clients to do web based shopping. Associations and people utilize this data to purchase the correct items and settle on business choices. This has influenced the spammers or unscrupulous agents to make bogus surveys and elevate their items to out-beat rivalries. To handle this issue, examines have been directed to define successful approaches to recognize the spam surveys. Different spam recognition strategies have been presented in which a large portion of them separates significant highlights from the content or utilized AI procedures. In this paper, named spam detection system, which uses spam features for demonstrating review data sets as heterogeneous information frameworks to design spam identification method into a group of issue. Using the criticalness of spam features help we to obtain good outcomes regarding different metrics on review data sets. The contribution work is when user search question it will show all n-no of items just as suggestion of the item.Keywords— Fake Review, Machine Learning, Social Media, Social Network, Spammer, Spam Review