Single-Pass Algorithms for Mining Frequency Change Patterns with Limited Space in Evolving Append-Only and Dynamic Transaction Data Streams
نویسندگان
چکیده
In this paper, we propose an online single-pass algorithm MFC-append (Mining Frequency Change patterns in append-only data streams) for online mining frequent frequency change items in continuous append-only data streams. An online space-efficient data structure called ChangeSketch is developed for providing fast response time to compute dynamic frequency changes between data streams. A modified approach MFCdynamic (Mining Frequency Change patterns in dynamic data streams) is also presented to mine frequency changes in dynamic data streams. The theoretic analyses show that our algorithms meet the major performance requirements of single-pass, bounded storage, and real time for streaming data mining.
منابع مشابه
Online Mining Changes of Items over Continuous Append-only and Dynamic Data Streams
Online mining changes over data streams has been recognized to be an important task in data mining. Mining changes over data streams is both compelling and challenging. In this paper, we propose a new, single-pass algorithm, called MFC-append (Mining Frequency Changes of append-only data streams), for discovering the frequent frequency-changed items, vibrated frequency changed items, and stable...
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