For the average biologist, hands-on literature mining currently means a keyword search in
PubMed. However, methods for extracting biomedical facts from the scientific literature have …

With biomedical literature increasing at a rate of several thousand papers per week, it is
impossible to keep abreast of all developments; therefore, automated means to manage the …

Text mining is a new and exciting area of computer science research that tries to solve the
crisis of information overload by combining techniques from data mining, machine learning …

This paper describes an application of a simple kNN approach to a novel classification
problem with an unbalanced class distribution. We discuss here one particular problem …

This handbook provides a thorough overview of the current state of knowledge in this area.
The first part of the book includes nine surveys and tutorials on the principal data mining …

Background Lately, there has been a great interest in the application of information
extraction methods to the biomedical domain, in particular, to the extraction of relationships …

Background The goal of the first BioCreAtIvE challenge (Critical Assessment of Information
Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of …

Abstract Background Advanced Text Mining (TM) such as semantic enrichment of papers,
event or relation extraction, and intelligent Question Answering have increasingly attracted …

The TREC Genomics Track implemented a new task in 2006 that focused on passage
retrieval for question answering using full-text documents from the biomedical literature. A …

We use machine learning tools for the design and discovery of ABO3-type perovskite oxides
for various energy applications, using over 7000 data points from the literature. We …