This is the home page of the ParsCit project, which performs reference string parsing, sometimes also called citation parsing or citation extraction. It is architected as a supervised machine learning procedure that uses Conditional Random Fields as its learning mechanism. You can download the code below, parse strings online, or send batch jobs to our web service (coming soon!). The code contains both the training data, feature generator and shell scripts to connect the system to a web service (used here too).
G. Sautter, und K. Böhm. Proceedings of the Second International Conference on Theory and Practice of Digital Libraries, Seite 370--382. Berlin, Heidelberg, Springer-Verlag, (2012)
P. Bitzer, F. Weiß, und J. Leimeister. Eighth International Conference on Design Science Research in Information Systems and Technology (DESRIST), Helsinki, Finland (accepted for publication), (2013)
A. Hotho, R. Jäschke, C. Schmitz, und G. Stumme. Proceedings of the First Conceptual Structures Tool Interoperability Workshop at the 14th International Conference on Conceptual Structures, Seite 87-102. Aalborg, Aalborg Universitetsforlag, (2006)