Learning CP-Nets Structure From Preference Data Streams

With the sharp increase of digital data emerging at present, the data in new applications are generated fast. Continuous cumulative data have gradually become massive and difficult to be handled due to limited workspace and limited amount of time. The conventional learning conditional preference net...

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Veröffentlicht in:	IEEE access 2018, Vol.6, p.56716-56726
Hauptverfasser:	Liu, Zhaowei, Zhong, Zhaolin, Zhang, Chenghui, Yu, Yanwei, Liu, Jinglei
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clustering algorithms Complexity theory Data mining Data models data streams Data transmission Digital data Digital media dynamic CP-net Heuristic algorithms incremental approach Machine learning Microsoft Windows Preference learning
Online-Zugang:	Volltext
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