Traditional relation extraction methods require pre-specified relations and relation-specific human-tagged examples. Bootstrapping systems significantly reduce the number of tr...
Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, Ji-...
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...
Background: The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order...
Angus Roberts, Robert J. Gaizauskas, Mark Hepple, ...
Biomedical entity extraction from unstructured web documents is an important task that needs to be performed in order to discover knowledge in the veterinary medicine domain. In ge...
Svitlana Volkova, Doina Caragea, William H. Hsu, J...
This paper introduces the problem of matching people names to their corresponding social network identities such as their Twitter accounts. Existing tools for this purpose build u...
Gae-won You, Seung-won Hwang, Zaiqing Nie, Ji-Rong...