UPPC - Urdu Paraphrase Plagiarism Corpus
Paraphrase plagiarism is a significant and widespread problem and research shows that it is hard to detect. Several methods and automatic systems have been proposed to deal with it. However, evaluation and comparison of such solutions is not possible because of the unavailability of benchmark corpora with manual examples of paraphrase plagiarism. To deal with this issue, we present the novel development of a paraphrase plagiarism corpus containing simulated (manually created) examples in the Urdu language - a language widely spoken around the world. This resource is the first of its kind developed for the Urdu language and we believe that it will be a valuable contribution to the evaluation of paraphrase plagiarism detection systems.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Automatically Ranked Russian Paraphrase Corpus for Text Generation
The article is focused on automatic development and ranking of a large corpus for Russian paraphrase generation which proves to be the first corpus of such type in Russian computational linguistics. Existing manually ann…
Paraphrase GenerationSentenceSentence SimilarityText GenerationPerPaDa: A Persian Paraphrase Dataset based on Implicit Crowdsourcing Data Collection
In this paper we introduce PerPaDa, a Persian paraphrase dataset that is collected from users' input in a plagiarism detection system. As an implicit crowdsourcing experience, we have gathered a large collection of origi…
Paraphrase IdentificationDo Language Models Plagiarize?
Past literature has illustrated that language models (LMs) often memorize parts of training instances and reproduce them in natural language generation (NLG) processes. However, it is unclear to what extent LMs "reuse" a…
Language ModellingMemorizationText GenerationMethods for Detecting Paraphrase Plagiarism
Paraphrase plagiarism is one of the difficult challenges facing plagiarism detection systems. Paraphrasing occur when texts are lexically or syntactically altered to look different, but retain their original meaning. Mos…
Corpus-Based Paraphrase Detection Experiments and Review
Paraphrase detection is important for a number of applications, including plagiarism detection, authorship attribution, question answering, text summarization, text mining in general, etc. In this paper, we give a perfor…
Authorship AttributionDeep LearningModel SelectionQuestion Answering+3