Atypon ’ s Artificial Intelligence R & D Fuels Four More BioASQ Awards in Semantic Technologies

For the fifth year in a row, Atypon has placed in the widely respected International BioASQ Awards competition. Atypon’s ongoing research and development (R&D) into artificial intelligence technologies led to four awards for four different semantic technology categories in the 2017 BioASQ Challenge. BioASQ organizes international contests in biomedical semantic indexing and question answering (QA) to help advance technologies that make it faster and easier for researchers to find the most relevant and actionable information from within the vast corpus of published biomedical research. Atypon’s R&D in machine learning and natural language processing—two branches of artificial intelligence—contributed to their award-winning semantic technologies. The R&D team’s work in the areas of recommender systems and knowledge representation—specifically, entity recognition, entity extraction, semantic search, search augmentation, and publication knowledge graphs—is also expanding the search and discovery capabilities of Literatum, the company’s online publishing platform. Entity recognition, a type of semantic enrichment, uses deep inference and reasoning to improve the accuracy, speed, and ease with which content can be automatically assessed and classified. Entity extraction, another type of semantic enrichment,  will be used to automatically add funding and grant information to enrich an article’s metadata, as well as to individuate compound figures and t...
Source: News from STM - Category: Databases & Libraries Authors: Tags: Digital Featured Source Type: news