Generating vector-based recommendations

Abstract

Techniques are described herein for performing generation of vector-based recommendations for entities. One or more embodiments address the challenge of generating recommendations for entities lacking sufficient recommendation generation input data. Unlike traditional collaborative filtering methods, various embodiments leverage content filtering techniques to make tailored and relevant recommendations for entities. By analyzing entity attributes and generating entity attribute vectors in an N-dimensional space, this system identifies the most suitable transactions by determining the closest neighbors in this space, thereby enhancing the accuracy and effectiveness of recommendations for entities associated with insufficient recommendation generation input data within the platform.