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中文摘要：
为提高具有先验知识样本的学习效率，本文在吸引子传播聚类模型基础上，引入半监督学习策略，并综合考虑样本动态信息变化，融合多指标面板数据，提出智能信息处理的多指标面板数据聚类模型。选取30家房地产业上市公司2009—2013年相关财务数据，利用此模型进行聚类和绩效评价分析。结果表明，智能信息处理的多指标面板数据聚类模型能更加有效地区分样本类别特征，可为上市公司绩效评价、金融管理与决策提供一个更加有效的方法和手段。
英文摘要：
In this paper, to affinity propagation clustering model, semi-supervised learning strategiesis introduced on the basis of the original model in order to improve the learning efficiency of sampleswith prior knowledge. And then a clustering model by intelligent information processing is proposedin this paper, which fuses multivariable panel data and considers sample information dynamic change.This article analyzes 30 real estate industry listed companies multivariable panel data in 2009-2013, theresults show that the model can provide a more effective method and means for financial management,performance evaluation and decision making.
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An Improved Affinity Propagation Clustering Algorithm Based on Entropy Weight Method and Principal C
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