Webinar – Can machine learning technologies be useful to create or complete ontologies in agriculture?
CGIAR Webinar by the Platform for Big Data in Agriculture’s Community of Practice on Ontologies – Can machine learning technologies be useful to create or complete ontologies in agriculture?
Expert in information systems design, data analysis and capacity building
Milko Škofič is a systems analyst with over 20 years of experience in design, development and implementation of plant genetic resources and forestry information systems. He has extensive experience in collecting, aggregating and analyzing data from heterogeneous and geographically dispersed scientific networks. Currently he supports the creation of national information platforms for nutrition in 10 countries.
Senior research fellow at the University of Sheffield
Dr. Diana Maynard is a senior research fellow at the University of Sheffield, UK, where she has been researching and developing tools for text mining and social-media analysis since 2000. She is one of the key developers of the widely used open source Natural Language Processing (NLP) toolkit GATE, and has special interests in multilinguality, social media, and sentiment analysis.
Research associate at the University of Sheffield
Xingyi Song is a research associate at the Natural Language Processing (NLP) group (GATE Team) managed by Prof. Kalina Bontcheva, working in the biomedical domain name/entity and sentiment recognition and analysis. He holds a PhD from the University of Sheffield in Training Machine translation for human acceptability. Song’s work mainly focuses on machine translation, natural language processing, and machine learning.
June 12, 2019
Ontologies Community of Practice
CGIAR Platform for Big Data in Agriculture