Document (#42300)

Author

Muneer, I.
Sharjeel, M.
Iqbal, M.
Adeel Nawab, R.M.
Rayson, P.

Title

CLEU - A Cross-language english-urdu corpus and benchmark for text reuse experiments

Source

Journal of the Association for Information Science and Technology. 70(2019) no.7, S.729-741

Year

2019

Abstract

Text reuse is becoming a serious issue in many fields and research shows that it is much harder to detect when it occurs across languages. The recent rise in multi-lingual content on the Web has increased cross-language text reuse to an unprecedented scale. Although researchers have proposed methods to detect it, one major drawback is the unavailability of large-scale gold standard evaluation resources built on real cases. To overcome this problem, we propose a cross-language sentence/passage level text reuse corpus for the English-Urdu language pair. The Cross-Language English-Urdu Corpus (CLEU) has source text in English whereas the derived text is in Urdu. It contains in total 3,235 sentence/passage pairs manually tagged into three categories that is near copy, paraphrased copy, and independently written. Further, as a second contribution, we evaluate the Translation plus Mono-lingual Analysis method using three sets of experiments on the proposed dataset to highlight its usefulness. Evaluation results (f1=0.732 binary, f1=0.552 ternary classification) indicate that it is harder to detect cross-language real cases of text reuse, especially when the language pairs have unrelated scripts. The corpus is a useful benchmark resource for the future development and assessment of cross-language text reuse detection systems for the English-Urdu language pair.

Content

Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24074.

Theme

Computerlinguistik

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