Neil Ireson, Fabio Ciravegna, Marie Elaine Califf, Dayne Freitag, Nicholas Kushmerick, Alberto Lavelli: Evaluating Machine Learning for Information Extraction, 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 7-11 August, 2005
TeSSI® (Terminology Supported Semantic Indexing) is a state-of-the-art tool that improves upon the existing search and retrieval tools by extracting the meaning out of medical free text and placing the resulting medical ‘concepts’ in the document ind
This is the project page for SecondString, an open-source Java-based package of approximate string-matching techniques. This code was developed by researchers at Carnegie Mellon University from the Center for Automated Learning and Discovery, the Department of Statistics, and the Center for Computer and Communications Security.
SecondString is intended primarily for researchers in information integration and other scientists. It does or will include a range of string-matching methods from a variety of communities, including statistics, artificial intelligence, information retrieval, and databases. It also includes tools for systematically evaluating performance on test data. It is not designed for use on very large data sets.
The cb2Bib is a tool for rapidly extracting unformatted, or unstandardized bibliographic references from email alerts, journal Web pages, and PDF files.