Very well know that the complexity and volume of the data is increasing rapidly in some Crowdsourcing websites. The term Crowdsourcing means the action of outsourcing tasks, traditionally performed by an employee or contractor, which are now performed by a large group of people. It is more expensive and more time consuming process because of increase in rate of submission and so short listing the winners. Data submitted by crowdsourcing websites can be noisy, inconsistent. To overcome this problems related to data one of the method was proposed which named as text mining method; this method performs the number of operations like extraction of data, preprocessing process, tf-idf calculation and calculation of similarity. Results obtained by existing system shows that k-means algorithm with text mining methods do not do the entire trick of evaluating submissions. Hence proposed system uses hierarchical clustering algorithm with text mining methods and classification for relation submission to overcome the problems present in the existing system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.