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Due to the explosive growth of short text on various social media platforms, short text stream clustering has become an increasingly prominent issue. Unlike traditional text streams, short text stream data present the following characteristics short length, weak signal, high volume, high velocity, topic drift, etc. Existing methods cannot simultaneously address two major problems very well inferring the number of topics and topic drift. Therefore, we propose a dynamic clustering algorithm for short text streams based on the Dirichlet proce
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