Nowadays most important developments in machine translation (MT) are achieved via combining data-driven and rule-based techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical MT paradigms, or the incorporation of data-driven components into rule-based paradigms, or statistical and rule-based pre- and post-processing for both types of MT architectures. The volume providesan overview of the field, as well as the latest relevant research conducted by linguists and practitioners from...