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

Cities:

  • 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.
http://docs.prediction.io/community/showcase/

Description:

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.

Dataset:

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

Demo link:

http://yelpio.hongo.wide.ad.jp/

http://zorovn.hongo.wide.ad.jp/

Link

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