Paper Info
Title
Automatic specialized vs. non-specialized sentence differentiation
Abstract
Compilation of Languages for Specific Purposes (LSP) corpora is a task which is fraught with several difficulties (mainly time and human effort), because it is not easy to discern between specialized and non-specialized text. The aim of this work is to study automatic specialized vs. non-specialized sentence differentiation. The experiments are carried out on two corpora of sentences extracted from specialized and non-specialized texts. One in economics (academic publications and news from newspapers), another about sexuality (academic publications and texts from forums and blogs). First we show the feasibility of the task using a statistical n-gram classifier. Then we show that grammatical features can also be used to classify sentences from the first corpus. For such purpose we use association rule mining.
Year
DOI
Venue
2011
10.1007/978-3-642-19437-5_22
CICLing (2)
Keywords
Field
DocType
non-specialized sentence differentiation,association rule mining,statistical n-gram classifier,grammatical feature,specific purposes,human effort,academic publication,non-specialized text,association rule
Computer science,Newspaper,Association rule learning,Artificial intelligence,Natural language processing,Classifier (linguistics),Linguistics,Sentence,Human sexuality
Conference
Volume
ISSN
Citations 
6609
0302-9743
1
PageRank 
References 
Authors
0.37
1
6
Name
Order
Citations
PageRank
Iria da Cunha114516.51
M. Teresa Cabré2102.77
Eric SanJuan3487.07
Gerardo Sierra47822.35
Juan-Manuel Torres-Moreno535951.36
Jorge Vivaldi67715.17