Document Type
Conference Proceeding
Publication Date
11-2006
Abstract
We address the issue of extracting implicit and explicit relationships between entities in biomedical text. We argue that entities seldom occur in text in their simple form and that relationships in text relate the modified, complex forms of entities with each other. We present a rule-based method for (1) extraction of such complex entities and (2) relationships between them and (3) the conversion of such relationships into RDF. Furthermore, we present results that clearly demonstrate the utility of the generated RDF in discovering knowledge from text corpora by means of locating paths composed of the extracted relationships.
Repository Citation
Ramakrishnan, C.,
Kochut, K.,
& Sheth, A. P.
(2006). A Framework for Schema-Driven Relationship Discovery from Unstructured Text. Lecture Notes in Computer Science, 4273, 583-596.
https://corescholar.libraries.wright.edu/knoesis/712
DOI
10.1007/11926078_42
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 5th International Semantic Web Conference, Athens, GA, November 5-9, 2006.
Video of the presentation can be found at http://videolectures.net/iswc06_ramakrishnan_fsdrd/.
Attached is the unpublished, author's version of this proceeding. The final publication is available at Springer via http://dx.doi.org/10.1007/11926078_42.