The explosive growth of biomedical literature has created a rich source of knowledge, such
as that on protein-protein interactions (PPIs) and drug-drug interactions (DDIs), locked in …

Distributed word representations have become an essential foundation for biomedical
natural language processing (BioNLP), text mining and information retrieval. Word …

Biomedical relation extraction aims to uncover high‐quality relations from life science
literature with high accuracy and efficiency. Early biomedical relation extraction tasks …

The DDIExtraction 2013 task concerns the recognition of drugs and extraction of drugdrug
interactions that appear in biomedical literature. We propose two subtasks for the …

The management of drug–drug interactions (DDIs) is a critical issue resulting from the
overwhelming amount of information available on them. Natural Language Processing …

Biomedical relation extraction can automatically extract high-quality biomedical relations
from biomedical texts, which is a vital step for the mining of biomedical knowledge hidden in …

Background Automated extraction of protein-protein interactions (PPI) is an important and
widely studied task in biomedical text mining. We propose a graph kernel based approach …

A vast amount of scientific information is encoded in natural language text, and the quantity
of such text has become so great that it is no longer economically feasible to have a human …

Due to an enormous number of scientific publications that cannot be handled manually,
there is a rising interest in text-mining techniques for automated information extraction …

State-of-the-art methods for protein-protein interaction (PPI) extraction are primarily feature-
based or kernel-based by leveraging lexical and syntactic information. But how to …