Title :
Detecting the Same Text in Different Languages
Author :
Koroutchev, Kostadin ; Cebrián, Manuel
Author_Institution :
Depto. de IngenierÃ\xada Informática, Universidad Autónoma de Madrid, 28049 Madrid, Spain. k.koroutchev@uam.es
Abstract :
Compression based similarity distances have the main drawback of needing the same coding scheme for the objects to be compared. When two texts are translated, there exists significant similarity with no literal coincidence. In this article, we present an algorithm that compares the redundancy structure of the data extracted by means of a Lempel- Ziv compression scheme. Each text is presented as a graph and two texts are considered similar with our measure if they have the same referential topology when compressed. We give empirical evidence that this measure detects similarity between data coded in different languages.
Keywords :
Compression algorithms; Computer science education; Conferences; Data mining; Entropy; Humans; Information theory; Length measurement; Object detection; Topology;
Conference_Titel :
Information Theory Workshop, 2006. ITW '06 Chengdu. IEEE
Conference_Location :
Chengdu, China
Print_ISBN :
1-4244-0067-8
Electronic_ISBN :
1-4244-0068-6
DOI :
10.1109/ITW2.2006.323816