Abstract
AbstractWe focus on searching similar data streams. Recent works regard the latest W items in a data stream as a set and reduce the problem to set similarity search. This paper uniquely studies similarity search for text streams and treats evolving sets composed of texts. We formulate a new continuous range search problem named the CTS problem to find all the text streams from the database whose similarity to the query becomes larger than a threshold \(\epsilon \). The CTS is challenging because it allows both the query and the database to change dynamically.KeywordsData streamSimilarity searchText setsInverted indexPruning
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