Automatic Arabic Text Summarization Based on Fuzzy Logic

The unprecedented growth in the amount of online information available in many languages to users and businesses, including news articles and social media, has made it difficult and time consuming for users to identify and consume sought after content. Hence, automatic text summarization for various languages to generate accurate and relevant summaries from the huge amount of information available is essential nowadays. Techniques and methodologies for automatic Arabic text summarization are still immature due to the inherent complexity of the Arabic language in terms of both structure and morphology. This work attempts to improve the performance of Arabic text summarization. We propose a new Arabic text summarization approach based on a new noun extraction method and fuzzy logic. The proposed summarizer is evaluated using EASC corpus and benchmarked against popular state of the art Arabic text summarization systems. The results indicate that our proposed Fuzzy logic approach with noun extraction outperforms existing systems.

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