Title A Large-Scale Resource for Storing and Recognizing Technical Terminology
Author(s) Henk Harkema, Robert Gaizauskas, Mark Hepple, Neil Davis, Yikun Guo, Angus Roberts, Ian Roberts

Department of Computer Science, University of Sheffield, Regent Court 211, Portobello Street, Sheffield, S1 4DP, UK

Session O5-T
Abstract This paper discusses the design and implementation of Termino, a large-scale terminological resource for text processing. Dealing with terminology is a difficult but unavoidable task for natural language processing applications, such as information extraction in technical domains. Complex, heterogeneous information must be stored about large numbers of terms. At the same time term recognition must be performed in realistic time. Termino attempts to reconcile this tension by maintaining a flexible, extensible relational database for storing terminological information and compiling finite state machines from this database to do term recognition.
Keyword(s) Terminology, text processing, databases, finite state machines, term recognition
Language(s) English
Full Paper 621.pdf