Tag Archives: recommendation

Yelp new challenge dataset

Yelp has been published new challenge dataset on February 9th.

Yelp Dataset Challenge is doubling up: Added 10 cities across 4 countries! 

The Challenge Dataset:

  • 1.6M reviews and 500K tips by 366K users for 61K businesses
  • 481K business attributes, e.g., hours, parking availability, ambience.
  • Social network of 366K users for a total of 2.9M social edges.
  • Aggregated check-ins over time for each of the 61K businesses


  • U.K.: Edinburgh
  • Germany: Karlsruhe
  • Canada: Montreal and Waterloo
  • U.S.: Pittsburgh, Charlotte, Urbana-Champaign, Phoenix, Las Vegas, Madison

New challenge questions

Continue reading

My recent work in Recommendation System

Need time to write up.


Yelp is an online urban guide that helps people find recommended destinations based on the informed opinions and reviews of a community.

Goal: the high level goal of this project is to apply existing built-in PredictionIO engines to a new domain and new dataset.

For this project you will build a restaurant recommendation engine (see Yelp) using built-in Item Recommendation engine and the Yelp dataset.


Yelp dataset via Kaggle – https://www.kaggle.com/c/yelp-recsys-2013/data

Demo link:




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