Title: Empirical Distributional Semantics: Methods and Biomedical Applications 1.5 Rule-based Methods for Text Processing 2. Existing Applications of Distributional Semantics 2.4 Bilingual Information Extraction 2.7 Taxonomy Construction and Validation 3.1 Gene Clustering Using Medline Abstracts

Over the past fifteen years, a range of methods have been developed that are able to learn human-like estimates of the semantic relatedness between terms from the way in which these terms are distributed in a corpus of unannotated natural language text. These methods have also been evaluated in a number of applications in the cognitive science, computational linguistics and the information retrieval literatures. In this paper, we review the available methodologies for derivation of semantic relatedness from free text, as well as their evaluation in a variety of biomedical and other applications. Recent methodological developments, and their applicability to several existing applications are also discussed.