A multi-dimensional time series algorithm for personalised recommendation in an innovation and entrepreneurship resource library

Key Points

• The research aims to develop a multi-dimensional algorithm to provide personalized resource recommendations.
• Developed a time series algorithm
• Assessed its relevance in resource library context
• Tested algorithm effectiveness on user data
• Improved accuracy in personalized recommendations
• Enhanced user engagement with resource library
• Demonstrated better resource matching for users