Abstract
In the area of recommendation system, clustering is an effective way to find similar users and reduce the complexity of recommendation algorithm. A good clustering result has two characteristics: maximizing compactness within cluster and maximizing separation between clusters. Following laws of attraction and repulsion, electric charges in an electric potential field have the same feature as clusters. Based on potential field, an improved Fuzzy C-Means (FCM) clustering algorithm is proposed, which is called EFCM (Electrical FCM). This algorithm combines the basic electrical rules of potential field, Coulomb's law and data field theory to obtain better clustering results. The experiment results show that the improved EFCM algorithm not only obtains good initial cluster centers, but also helps to improve the process of iterative updating.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: DEStech Transactions on Computer Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
