Time-based discovery in biomedical literature: mining temporal links

Linking biomedical concepts is one of the task of the literature-based discovery and permits to identify interesting and hidden relations between seemingly unconnected concepts or entities. Most of existing approaches rely on the assumption that data and underlying literature are static or considered as unchangeable domains. While scientific literature is instead an intrinsically dynamic domain and can change over time: publications may report studies on the same topic conducted one after another over time. In this work, we investigate the task of analysing biomedical literature under the temporal dimension in order to mine links among concepts over time. This provides us a means to unearth linkages which have not been discovered when observing the literature as static but which may have developed over time, when considering the dynamic nature. We propose a computational solution which, assuming a time interval-based discretisation of the literature, explores the spaces of association rules mined in the intervals and chains these rules on the basis of the concept generalisation and information theory criteria. The application to the Swanson's discoveries shows the possibility of the method to re-discover known connections in biomedical terminology. Experiments and comparisons with alternative techniques highlight the additional peculiarities offered by this work.