Best Match: New relevance search for PubMed

PubMed is a free search engine for biomedical literature accessed by millions of users from around the world each day. With the rapid growth of biomedical literature, finding and retrieving the most relevant papers for a given query is increasingly challenging. We have developed Best Match, a new relevance search algorithm for PubMed that leverages the intelligence of our users and cutting-edge machine-learning technology as an alternative to the traditional date sort order. The Best Match algorithm is trained with past user searches with dozens of relevance-ranking signals (factors) and demonstrates state-of-the-art retrieval performance in benchmarking experiments as well as an improved user experience in real-world testing.