Multiple recommendation systems at Wayfair use collaborative filtering based models to understand user behavior and identify like-minded customers. Despite its success, collaborative filtering has a few significant drawbacks, such as the cold start problem and a limited scope of recommendable products. By leveraging image based product embeddings, Wayfair… Read more
Search has long been an essential tool for Wayfair that enables users to discover products among millions. While we offer great text and faceted search, those features can only go so far. It can be difficult to precisely describe an item in mind, especially in a way search engines can……
That’s a heat map of 3 months of Wayfair North American orders, exported via Logstash from our relational orders database into Elasticsearch, and visualized with Kibana… Read more
On the search and recommendations team at Wayfair, we like to think of ourselves as sophisticated men and women of the world. We have speakers of French, Chinese, Hebrew, German and Persian in the crew. Some of us host couchsurfers at our swanky apartments, and then turn around and couchsurf……
Me: Doug, what are you doing? Doug: Solving the problem of class struggle with one of Greg‘s classifiers. Me: Karl Marx should call his office. What do you mean by that? Doug: Let me explain…
We use the Apache SOLR search platform behind the scenes at Wayfair. Sometimes, when vanilla SOLR doesn’t quite do what we want, we improve it for our purposes. When we suspect that others might have the same purposes, and we think that we have solved… Read more
