A three-way approach for learning rules in automatic knowledge-based topic models

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• 作者：Muhammad Taimoor Khan^a ; ^b ; ^{taimoor.khan@nu.edu.pk} ; Nouman Azam^a ; Shehzad Khalid^b ; JingTao Yao^c
• 关键词：Topic models ; Automatic knowledge-based models ; Game-theoretic rough sets ; Three-way decisions
• 刊名：International Journal of Approximate Reasoning
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：82
• 期：Complete
• 页码：210-226
• 全文大小：1401 K
• 卷排序：82

文摘

A three-way approach is proposed for selecting rules in automatic knowledge-based topic models. The selection of rules in the three-way approach is controlled based on a pair of thresholds. Effective thresholds are determined based on a tradeoff between the quantity of rules and the quality of the rules. The game-theoretic rough set (GTRS) model is used to implement the tradeoff.