Creating Scalable and Interactive Web Applications Using High Performance Latent Variable Models
This work addresses the need for more informative product comparisons for online shoppers, but it appears incremental as it builds on existing latent variable models and visualization techniques.
The authors tackled the problem of comparing Amazon products by developing a scalable system that uses latent variable models and dynamic visualization to provide fast, multifaceted comparisons. They demonstrated that their interface is at least as compact as Amazon's 'most helpful reviews' but far more informative, though no concrete performance numbers were provided.
In this project we outline a modularized, scalable system for comparing Amazon products in an interactive and informative way using efficient latent variable models and dynamic visualization. We demonstrate how our system can build on the structure and rich review information of Amazon products in order to provide a fast, multifaceted, and intuitive comparison. By providing a condensed per-topic comparison visualization to the user, we are able to display aggregate information from the entire set of reviews while providing an interface that is at least as compact as the "most helpful reviews" currently displayed by Amazon, yet far more informative.