Tuesday 16th June, 2015
2:00pm to 2:30pm
At OpenTable, we help diners find the best dining experiences, wherever they travel. One of the key problems for accomplishing this is providing personalized recommendations. We have been leveraging our large corpus of unstructured reviews to build models to improve the accuracy of these recommendations. We will discuss how we use Spark both for the training of our recommenders, and for the natural language processing of the reviews to generate topic models.
PhD DataScientist @OpenTable. Astrophysicist, #cosmology, #DataScience, #BayesImpact . Princeton, Berkeley, Coffee buff http://datamusing.info bio from Twitter
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