Last night I had the opportunity to speak at the Greenville Data Science & Analytics Meetup on “Building Search & Recommendation Engines“. It was a great opportunity to present a general introduction to Apache Solr, Search Engines, Relevancy, Recommendations, and generally building intelligent information retrieval systems. I appreciated the level of interest and insightful questions from everyone who attended, and I look forward to more great events from this group in the future!
Slides:
http://www.slideshare.net/treygrainger/building-search-and-recommendation-engines
Talk Abstract:
In this talk, you’ll learn how to build your own search and recommendation engine based on the open source Apache Lucene/Solr project. We’ll dive into some of the data science behind how search engines work, covering multi-lingual text analysis, natural language processing, relevancy ranking algorithms, knowledge graphs, reflected intelligence, collaborative filtering, and other machine learning techniques used to drive relevant results for free-text queries. We’ll also demonstrate how to build a recommendation engine leveraging the same platform and techniques that power search for most of the world’s top companies. You’ll walk away from this presentation with the toolbox you need to go and implement your very own search-based product using your own data.
