群体智慧集群集成
Wisdom of Crowds cluster ensemble
摘要：
群体智慧是社会科学中描述的一种现象，它提出了适用于人群的四个标准。有人声称，如果这些标准得到满足，那么由一个群体做出的总体决策往往会比其单个成员做出的决策更好。受此概念的启发，我们提出了一种新的反馈框架的集群集成问题，我们称之为智慧的人群集群包围（WOCCE）。虽然许多传统的集群集成方法集中在多样性最近被提出，WOCCE分析了必要的条件，为一群人展示这种集体智慧。这些标准包括用于生成主要结果的分散化标准、用于基本算法的独立性标准和用于集成成员的多样性标准。我们建议适当的程序来评估这些措施，并提出了一个新的措施来评估的多样性。我们评估的性能WOCCE对其他一些传统的基础算法，以及国家的最先进的集成方法。实验结果表明，与其他算法相比，WOCCE的聚合决策的效率。
英文摘要：
The Wisdom of Crowds is a phenomenon described in social science that suggests four criteria applicable to groups of people. It is claimed that, if these criteria are satisfied, then the aggregate decisions made by a group will often be better than those of its individual members. Inspired by this concept, we present a novel feedback framework for the cluster ensemble problem, which we call Wisdom of Crowds Cluster Ensemble (WOCCE). Although many conventional cluster ensemble methods focusing on diversity have recently been proposed, WOCCE analyzes the conditions necessary for a crowd to exhibit this collective wisdom. These include decentralization criteria for generating primary results, independence criteria for the base algorithms, and diversity criteria for the ensemble members. We suggest appropriate procedures for evaluating these measures, and propose a new measure to assess the diversity. We evaluate the performance of WOCCE against some other traditional base algorithms as well as state-of-the-art ensemble methods. The results demonstrate the efficiency of WOCCE's aggregate decision-making compared to other algorithms.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
