Paper: Learning to Annotate Scientific Publications

ACL ID C10-2053
Title Learning to Annotate Scientific Publications
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010

Annotating scientific publications with keywords and phrases is of great importance to searching, indexing, and cataloging such documents. Unlike previous studies that focused on user- centric annotation, this paper presents our investigation of various annotation characteristics on service-centric anno- tation. Using a large number of publicly available annotated scientific publica- tions, we characterized and compared the two different types of annotation processes. Furthermore, we developed an automatic approach of annotating scientific publications based on a machine learning algorithm and a set of novel features. When compared to other methods, our approach shows significant- ly improved performance. Experimental data sets and evaluation results are pub- licly availabl...