Abstract
This work introduces a survey for the Text Paraphrasing task. The survey covers the different types of tasks around text paraphrasing and mentions the techniques and models that are regularly used when approaching towards it, alongside the datasets that are used while training and evaluating the models. Text paraphrasing has an effective impact when it is used in other applications, so, the paper mentions some text paraphrasing applications. Also, this work proposes a new taxonomy that it is called Conditional Text Paraphrasing. To the best of our knowledge, this is the first work that shows varieties and sub-problems of the original text paraphrasing task. The target of this taxonomy is to expand the definition of the text paraphrasing by adding some conditional constraints as features that either control the paraphrase generation or discrimination. This expanded definition opens in mind a new domain for research in Natural Language Processing (NLP) and Machine Learning. Finally, some useful applications for the conditional text paraphrasing are represented.
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CITATION STYLE
Al-Ghidani, A. H., & Fahmy, A. A. (2018). Conditional text paraphrasing: A survey and taxonomy. International Journal of Advanced Computer Science and Applications, 9(11), 589–594. https://doi.org/10.14569/ijacsa.2018.091182
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