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ParaCap: paraphrase detection model using capsule network
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DOI：10.1007/s00530-020-00746-6.png)
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Abstract
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This paper is concerned withthe problem of paraphrase detection. For a number of applications, the ability to detect similar sentences, such as text mining, summary text, plagiarism detection, authorship authentication, and question answering, is important. Given two phrases, the goal is to detect whether they are identical semantically. This work involves a novel model namely, ParaCap, which uses capsule networks for the investigation of sentences. Capsule networks understand the spatial information (context, language, length of sentences and others) by using the instantiation parameters for the better results as compared to CNNs. For the objective, the Quora Question Pair dataset containing 404291 pairs of Quora Questions is being used. The ParaCap model outperforms many state-of-art methods, and also proves to be comparable to other techniques by achieving the accuracy of 89.19%.
Keywords:
Paraphrase identification
Text classification
Capsule networks
NLP
Plagiarism
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2.8K
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