Extractive Arabic Text Summarization Using PageRank and Word Embedding
Ghadir Alselwi,
Tuğrul Taşcı
Abstract:Research on graph-based automatic text summarization for Arabic, the official language of 26 nations with over 200 million speakers, as well as other prevalent languages, has recently increased due to the ability of these approaches to handle linguistic peculiarities such as complex morphological linkages. The present paper proposes a graph-based extractive Arabic text summarization (GEATS) technique that employs word embedding and PageRank algorithms for feature extraction and sentence ordering. The efficienc… Show more
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