Hotel Recommendation Engine

We built a hotel recommendation engine with an ensemble collaborative filtering approach. We pair this with beautiful, interactive data visualizations built on top of D3.js, running live in the browser to create a dynamic story with the data.

To build our hotel recommendation system, we first created a set of ratings, based on a weighted average of user actions associated with a particular hotel.

We applied the following models:

  1. Matrix Factorization
  2. Non-Negative Matrix Factorization
  3. Hierarchal Multilayer Model

We created a fully responsive web dashboard to host our visualizations. These visualizations include:

  1. Geographical Heat Maps of Quantitative Features
  2. Feature Histograms
  3. Topographical Higher-Dimensional representations of sparse matrix before training + dense matrix learned by model
  4. Network Graph Summarizing Recommendation Results

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