Abstract
Paraphrasing techniques aim to recognize, generate, or extract linguistic expressions that express the same meaning. These techniques affects positively or negatively the performance of many natural language-processing systems such as Question Answering, Summarization, Text Generation, and Machine Translation.... In this paper, we propose an efficient Arabic paraphrase recognizer based on kernel function and the specificity of terms, which is computed by term co-occurrence and term frequency - inverse document frequency. The experimental results show that our method outperforms the exiting methods based on similarity measures using a standard Arabic paraphrase database PPDB.
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Elfaik, H., Bekkali, M., Brahim, H., Lachkar, A. (2019). Arabic Paraphrasing Recognition Based Kernel Function for Measuring the Similarity of Pairs. In: Khoukhi, F., Bahaj, M., Ezziyyani, M. (eds) Smart Data and Computational Intelligence. AIT2S 2018. Lecture Notes in Networks and Systems, vol 66. Springer, Cham. https://doi.org/10.1007/978-3-030-11914-0_20
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DOI: https://doi.org/10.1007/978-3-030-11914-0_20
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