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Semi-Supervised Technical Term Tagging With Minimal User Feedback

Buitelaar, Paul
; 
Bordea, Georgeta
; 
QasemiZadeh, Behrang
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Identifiers
http://hdl.handle.net/10379/4383
 https://doi.org/10.13025/21294
Publication Date
2012
Keywords
Technical Term Tagging, Information Extraction, Machine Learning
Type
Conference Paper
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QasemiZadeh, B,Buitelaar, P,Chen, TQ,Bordea, G (2012) Semi-Supervised Technical Term Tagging With Minimal User Feedback LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Abstract
In this paper, we address the problem of extracting technical terms automatically from an unannotated corpus. We introduce a technology term tagger, that is based on Liblinear Support Vector Machines and employs linguistic features including Part of Speech tags and Dependency Structures, in addition to user feedback to perform the task of identification of technology related terms. Our experiments show the applicability of our approach as witnessed by acceptable results on precision and recall.
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Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Data Science Institute (Scholarly Articles)