Search-based recommendations at Politico
Ryan Kohl • Back to Haystack 2019
Over the past year, the POLITICO team has developed a recommendation system for our users, which recommends not only news content to read but also news topics to subscribe to. This talk will discuss our development path, including dead-ends and performance trade-offs. In the end, the team produced a system based on search technology (in our case, Elasticsearch) and refined by machine learning techniques to achieve a balance between personalization and serendipity.
An architect at POLITICO, Ryan spends his time building systems having to do with search, recommendation, natural language processing, and analytics. In his prior lives, he also worked with semantic web technologies, machine learning, ice cream, and grocery bagging techniques.