Titlebook: Rough Sets and Current Trends in Computing; 9th International Co Chris Cornelis,Marzena Kryszkiewicz,Lin Shang Conference proceedings 2014

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Mining Significant Granular Association Rules for Diverse Recommendationthe probability that users purchase or rate certain items. Unfortunately, the confidence-based approach tends to suggest popular items to users, and novel patterns are often ignored. In this paper, we propose to mine significant granular association rules for diverse and novel recommendation. Genera

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Incremental Three-Way Decisions with Incomplete Informationive regions. Rules generated by the three regions form three-way decision rules, which are acceptance, deferment and rejection decisions. The periodic updating of decision rules is required due to the dynamic nature of decision systems. Incremental learning technique is an effective way to solve the

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Want More? Pay More! monotonicity does not always hold in decision-theoretic rough set, the decision-monotonicity reduct may help us to increase both lower approximation and upper approximation. The experimental results in this paper tell us that by comparing with the original decision system, more cost is required wit

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An Incremental Clustering Approach Based on Three-Way Decisionsover time. To combat changes, we introduce a new incremental soft clustering approach based on three-way decisions theory in this paper. Firstly, an initial clustering algorithm is proposed by using representative points. Secondly, to eliminate the influence of the processing order on final incremen

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Determining Three-Way Decision Regions with Gini Coefficientsed as the acceptance, rejection, and non-commitment decision regions in three-way classification. Interpretation and determination of decision regions are one of the key issues of three-way decision and rough set theories. We investigate the relationship between changes in rough set regions and thei

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Cost-Sensitive Three-Way Decisions Model Based on CCAo three parts: the positive region POS(X), the negative region NEG(X) and the boundary region BND(X). But acquirement of a pair of thresholds is a challenge. In this paper, we propose a new method to get the thresholds of three-way decisions model. We introduce loss function into three-way decisions

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