Using Artificial Intelligence to extract information on pathogen characteristics from scientific publications

Health risk assessment of environmental exposure to pathogens requires complete and up to date knowledge. With the rapid growth of scientific publications and the protocolization of literature reviews, an automated approach based on Artificial Intelligence (AI) techniques could help extract meaningful information from the literature and make...

Language-consistent Open Relation Extraction: from Multilingual Text Corpora

Open Relation Extraction (ORE) aims to find arbitrary relation tuples between entities in unstructured texts. Even though recent research efforts yield state-of-the-art results for the ORE task by utilizing neural network based models, these works are solely focused on the English language. Methods were proposed to tackle the ORE task for...

Coner: A Collaborative Approach for Long-Tail Named Entity Recognition in Scientific Publications

Named Entity Recognition (NER) for rare long-tail entities as e.g. often found in domain-specific scientific publications is a challenging task, as typically the extensive training data and test data for fine-tuning NER algorithms is lacking. Recent approaches presented promising solutions relying on training NER algorithms in a iterative...

Learning Object Metadata Workflows for Description, Findability and Reusability Improvement

With the increase of online education, a good description of learning resources has become vital for educational resource sharing and reuse. Resource description has been under the spotlight in recent years. Educational platforms can benefit from good resource organisation and description, thereby providing a higher quality of services and...

Politags: Breaking the filter bubble by using information extraction techniques to enable diverse personalization

This research is aimed at breaking online political filter bubbles. We present a system that uses artificial intelligence and human computation to automatically collect article metadata on political content and thereby enables diverse personalization on content-serving platforms. This way, exploring alternative viewpoints could become as simple...

SmartPub: A Platform for Long-Tail Entity Extraction from Scientific Publications

This demo presents SmartPub, a novel web-based platform that supports the exploration and visualization of shallow meta-data (e.g., author list, keywords) and deep meta-data--long tail named entities which are rare, and often relevant only in specific knowledge domain--from scientific publications. The platform collects documents from different...