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).
J. Tang, M. Hong, J. Li, und B. Liang. International Semantic Web Conference, Volume 4273 von Lecture Notes in Computer Science, Seite 640-653. Springer, (2006)
Y. Jin, Y. Matsuo, und M. Ishizuka. Proceedings of the European Semantic Web Conference, ESWC2007, Volume 4519 von Lecture Notes in Computer Science, Springer-Verlag, (Juli 2007)
M. Kayed, und K. Shaalan. IEEE Transactions on Knowledge and Data Engineering18 (10):
1411--1428(2006)Member-Chia-Hui Chang and Member-Moheb Ramzy Girgis.
G. Gottlob, C. Koch, R. Baumgartner, M. Herzog, und S. Flesca. Proceedings of the Twenty-third ACM SIGACT-SIGMOD-SIGART Symposium
on Principles of Database Systems, June 14-16, 2004, Paris, France, Seite 1-12. ACM, (2004)