Authors:
Jing Ding
and
Daniel Berleant
Affiliation:
Iowa State University, United States
Keyword(s):
text mining, markup language, bioinformatics
Related
Ontology
Subjects/Areas/Topics:
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Modeling Concepts and Information Integration Tools
;
Modeling Formalisms, Languages and Notations
;
Requirements Analysis And Management
Abstract:
With the rapid growth of electronically available scientific literature, text mining is attracting increasing attention. While numerous algorithms, tools, and systems have been developed for extracting information from text, little effort has been focused on how to mark up the information. We present the design of a standoff, object-oriented markup language (called SOOML), which is simple, expressive, flexible, and extensible, satisfying the demanding needs of biomedical text mining.