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Detection of Translator Stylometry using Pair-wise Comparative Classification and Network Motif Mining ...
El-Fiqi, Heba
. - : UNSW Sydney, 2013
Abstract:
Stylometry is the study of the unique linguistic styles and writing behaviours of individuals. The identification of translator stylometry has many contributions in fields such as intellectual-property, education, and forensic linguistics. Despite the research proliferation on the wider research field of authorship attribution using computational linguistics techniques, the translator stylometry problem is more challenging and there is no sufficient machine learning literature on the topic. Some authors even claimed that detecting who translated a piece of text is a problem with no solution; a claim we will challenge in this thesis. In this thesis, we evaluated the use of existing lexical measures for the translator stylometry problem. It was found that vocabulary richness could not identify translator stylometry. This encouraged us to look for non-traditional representations to discover new features to unfold translator stylometry. Network motifs are small sub-graphs that aim at capturing the local ...
Keyword:
C4.5
;
Classification Algorithms
;
Comparative Classification Problems
;
Computational Linguistics
;
Decision Trees
;
Machine learning
;
Network Motifs
;
Paired Classification
;
Parallel Translations
;
Pattern Recognition
;
PWC4.5
;
Social Network Analysis
;
Stylometry Analysis
;
Translator Stylometry Identification
URL:
https://dx.doi.org/10.26190/unsworks/16460
http://hdl.handle.net/1959.4/53020
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