Implementing K-Means Clustering and Collaborative Filtering to Enhance Sustainability of Project Repositories (Abstract Only)
Matthew R. Steuerer · 2016
Websites for dissemination of grant-funded projects can quickly become unsustainable once funding ends since they require significant human intervention to ensure that data are current and reliable. CABECTPortal is a website that maintains information about research projects that involve interdisciplinary pedagogical collaborations. It leverages social computational concepts and a machine learning algorithm, specifically k-means clustering, to improve the sustainability of dissemination efforts by engaging the research community in the process. Usability design concepts are integrated with throughout the site to enhance user motivation and engagement. This poster will present the machine learning algorithms that were implemented for the recommendation system used in CABECTPortal. Acknowledgment: This project is based on work supported by the National Science Foundation under NSF DUE Award# 1141170. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF).