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11#
發(fā)表于 2025-3-23 09:45:28 | 只看該作者
12#
發(fā)表于 2025-3-23 16:55:42 | 只看該作者
13#
發(fā)表于 2025-3-23 21:03:35 | 只看該作者
14#
發(fā)表于 2025-3-23 23:20:04 | 只看該作者
Rough Text Assisting Text Mining: Focus on Document Clustering Validitysome RST-based measures for the evaluation of decision systems. We will focus on the application of such concept in clustering validity, specifically cluster labeling and multi-document summarization. The experimental studies show that the proposed measures outperform several internal measures exist
15#
發(fā)表于 2025-3-24 05:06:05 | 只看該作者
16#
發(fā)表于 2025-3-24 09:12:07 | 只看該作者
17#
發(fā)表于 2025-3-24 14:22:43 | 只看該作者
,Erratum to: Vorbereitung. — Grundbegriffe,0] such a question was discussed and a solution was proposed. In this chapter we start from the ideas in [10] to sketch a method to design expert systems, probabilistic in nature. Indeed, we assume that the probability an individual satisfies a property is the percentage of similar individuals satis
18#
發(fā)表于 2025-3-24 17:39:08 | 只看該作者
19#
發(fā)表于 2025-3-24 20:27:46 | 只看該作者
,Informationsbewertung durch Me?systeme,gies generated by partitions, according to the Pawlak approach to rough set theory. In this partition context of a finite universe, typical of complete information systems, the probability space generated by the counting measure is analyzed, with particular regard to a local notion of rough entropy
20#
發(fā)表于 2025-3-25 00:53:16 | 只看該作者
Janna Teltemann,Reinhard Schunckts at the present time and study its evolution over the past 25 years. Our approach is more experimental and statistical rather than theoretical. It seems that these data are interesting in their own right as a reflection of the way in which the rough set research is done, apart from the mathematica
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