An HMM-based single character recovery (SCR) model is proposed in this paper to extract a large set of atomic abbreviations and their full forms from a text corpus. By an “atomic abbreviation,” it refers to an abbreviated word consisting of a single Chinese character. This task is important since Chinese abbreviations cannot be enumerated exhaustively but the abbreviation process for compound words seems to be compositional. One can often decode an abbreviated word character by character to its full form. With a large atomic abbreviation dictionary, one may be able to handle multiple character abbreviation problems more easily based on the compositional property of abbreviations.
