ParsCit: An open-source CRF Reference String and Logical Document Structure Parsing Package. This is the home page of the ParsCit project, which performs two tasks: 1) reference string parsing, sometimes also called citation parsing or citation extraction, and 2) logical structure parsing of scienfific documents. 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. The code contains both the training data, feature generator and shell scripts to connect the system to a web service (used on this web site).

References in zbMATH (referenced in 3 articles )

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  1. Kluegl, Peter; Toepfer, Martin; Lemmerich, Florian; Hotho, Andreas; Puppe, Frank: Exploiting structural consistencies with stacked conditional random fields (2013)
  2. Růžička, Michal; Sojka, Petr; Krejčíř, Vlastimil: Towards machine-actionable modules of a digital mathematics library. The example of DML-CZ (2013)
  3. Zou, Jie; Le, Daniel; Thoma, George R.: Locating and parsing bibliographic references in HTML medical articles (2010) ioport