50 citations · 68 across the 4 of their papers we have counts for
4 papers
PubMed Labs: An experimental platform for improving biomedical literature search
Nicolas Fiorini, Kathi Canese, Rostyslav Bryzgunov +9
PubMed is a freely accessible system for searching the biomedical literature, with approximately 2.5 million users worldwide on an average workday. We have recently developed PubMe…
Personalized neural language models for real-world query auto completion
Nicolas Fiorini, Zhiyong Lu
Query auto completion (QAC) systems are a standard part of search engines in industry, helping users formulate their query. Such systems update their suggestions after the user typ…
A Fast Deep Learning Model for Textual Relevance in Biomedical Information Retrieval
Sunil Mohan, Nicolas Fiorini, Sun Kim +1
Publications in the life sciences are characterized by a large technical vocabulary, with many lexical and semantic variations for expressing the same concept. Towards addressing t…
Bridging the Gap: Incorporating a Semantic Similarity Measure for Effectively Mapping PubMed Queries to Documents
Sun Kim, Nicolas Fiorini, W. John Wilbur +1
The main approach of traditional information retrieval (IR) is to examine how many words from a query appear in a document. A drawback of this approach, however, is that it may fai…