Background This article provides an overview of the first BioASQ challenge, a competition
on large-scale biomedical semantic indexing and question answering (QA), which took …

While collections of documents are often annotated with hierarchically structured concepts,
the benefits of these structures are rarely taken into account by classification techniques …

Efficient distributed numerical word representation models (word embeddings) combined
with modern machine learning algorithms have recently yielded considerable improvement …

Several natural language processing (NLP) tasks are defined as a classification problem in
its most complex form: Multi-label Hierarchical Extreme classification, in which items may be …

The classification of natural language texts has gained a growing importance in many real
world applications due to its significant implications in relation to crucial tasks, such as …

Hierarchical classification learning, which organizes data categories into a hierarchical
structure, is an effective approach for large-scale classification tasks. The high …

Classification systems are evaluated in a countless number of papers. However, we find that
evaluation practice is often nebulous. Frequently, metrics are selected without arguments …

Precision farming technologies are important for a stable supply of healthy food. Every year
farmers harvest a few amounts of crops because of the pests and diseases. Automatic …

ICD-9 (the Ninth Revision of International Classification of Diseases) is widely used to
describe a patient's diagnosis. Accurate automated ICD-9 coding is important because …

LSHTC is a series of challenges which aims to assess the performance of classification
systems in large-scale classification in aa large number of classes (up to hundreds of …