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Titlebook: Intelligent Decision Technologies 2017; Proceedings of the 9 Ireneusz Czarnowski,Robert J. Howlett,Lakhmi C. Ja Conference proceedings 2018

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發(fā)表于 2025-3-25 07:03:14 | 只看該作者
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發(fā)表于 2025-3-25 17:47:20 | 只看該作者
Manipulability of Majority Relation-Based Collective Decision Rulesy-proof. In other words, there are some situations when at least one agent can submit insincere ranking and change the final result in a way beneficial to him. We call this situation manipulable and using computer modelling we study 10 majority relation-based collective decision rules and compare th
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發(fā)表于 2025-3-25 22:00:21 | 只看該作者
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發(fā)表于 2025-3-26 00:26:43 | 只看該作者
A Hybrid Approach to Conceptual Classification and Ranking of Resumes and Their Corresponding Job Poers who have different fields of expertise and specialize in various domains. Accordingly, automatically extracting structured information from such resumes is needed not only to support the automatic matching between candidate resumes and their corresponding job offers, but also to efficiently rout
27#
發(fā)表于 2025-3-26 06:10:22 | 只看該作者
28#
發(fā)表于 2025-3-26 10:45:53 | 只看該作者
Dispersed System with Dynamically Generated Non–disjoint Clusters – Application of Attribute Selecti a previous work. The selection of attributes method, that is used, is based on the rough sets theory. At first, reducts of sets of attributes for local knowledge bases are generated and then the attributes that do not occur in the reducts are removed from the local bases. In the study, the accuracy
29#
發(fā)表于 2025-3-26 12:51:55 | 只看該作者
Generational Feature Elimination to Find All Relevant Feature Subset this paper, the all relevant feature selection method based on information gathered using generational feature elimination was introduced. The successive generations of feature subset were defined using . algorithm and in each step the subset of most important features were eliminated from the prim
30#
發(fā)表于 2025-3-26 17:40:51 | 只看該作者
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