Text Streaming Model
Text streaming model (TSM) is one of the fundamental problems in streaming model and text mining. It aims to process a sequence of text data that comes at a rate. In this model, text data does not take the form of arriving in multiple, continuous, rapid, time-varying data streams. Input text streaming D1, D2, …. arrives sequentially, one by one, and the aim of TSM is to analysis the streaming text data.
Mining the streaming data has attracted much attention of researchers in different areas due to its great industrial and commercial application potentials. Specifically, text streaming data models are of interest to the machine learning and data mining community. The world wide web has many text data, such as web pages, news-feeds, emails and blogs. And most of them are classical text streaming data. Then, how to model text streaming data is important.
Traditional text data model is Vector Space Model (VSM). One of the commonly used VSM is the Bag of...
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