A novel framework to improve the performance of crowdfunding platforms

This work presents a framework for evaluating and promoting campaigns that are launched over a crowdfunding platform. Campaigns are evaluated on the basis of campaign features and pledge performance. To promote a campaign, a recommender model is designed that filters campaigns to be promoted using association rule mining and based on backer's interests. Framework also assesses creators' using their past records and their profile text. This system deals with the issues faced by three stakeholders of crowdfunding and strives to satisfy their requirements and maximizes the utility of tool.