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In this paper, we present and analyze the results of the application of Arabic query-based text summarization system - AQBTSS - in an attempt to produce a query-oriented summary for a single Arabic document. For this task, we adapted the traditional vector space model (VSM) and the cosine similarity measure to find the most relevant passages extracted form Arabic document to produce a text summary. We aim at using the short summaries in some natural language (NL) tasks such as generating answers for Arabic open domain question answering system (AQAS) as well as experimenting with categorizing Arabic scripts. The obtained results indicate that our simple approach for text summarization is promising.