TORONTO – Online video discovery and distribution company Vubble is teaming up with Seneca College on a new research project targeted at advancing video categorization.
Vubble said that it will collaborate with Dr. Vida Movahedi and student research assistants from Seneca’s School of Information and Communications Technology to develop a machine-learning algorithm that will automatically identify the subject area of the curated videos in the Vubble library.
The year-long applied research project will be supported by SOSCIP, an R&D consortium based in Ontario that helps Canadian companies drive innovation with data science. SOSCIP is supported through investment from FedDev Ontario, the Province of Ontario and others.
“This video categorization research project will be a significant advancement of Vubble’s ability to automate the accurate categorization of video,” said Vubble CEO Tessa Sproule, in the news release. “Video curation is at the core of our business and the ability to automate elements within our curation process is key to growing our company.”
“Seneca’s School of ICT is a data analytics powerhouse. Working with Vubble is an excellent opportunity for Seneca faculty and students to apply our data analytics capabilities to video categorization, using machine-learning,” added Seneca’s Dean, Applied Research, Innovation and Entrepreneurship , Vanessa Williamson, in the release. “Seneca is the first college member of SOSCIP and we are thrilled that our collaboration with Vubble will be our first project funded through the consortium.”
Used by media companies and educational publishers, Vubble’s platform curates, assesses and distributes personalized feeds of video content, separating the video wheat from all that chaff, as it were, using advanced AI technology and human curation.
