Speech image data mining algorithm based on multimodal decision fusion

Cong Lu, Danxing Wang, Daquan Zhang, Aiqun Yu
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Abstract

This paper proposes a data mining algorithm based on multimodal decision fusion, which is mainly used to solve the correlation relationship of multi-level and multi-level multimodal data, the algorithm combines the methods of statistics, queueing study, machine learning and Bayesian decision fusion, compared with the results obtained by single modality, single data and single method, the algorithm proposed in this paper retains the information contained in the data to the maximum extent, and the algorithm is applied to the analysis of both numerical and text-based data. The proposed algorithm can be further extended by modifying the data types and methods to form new methods.
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基于多模态决策融合的语音图像数据挖掘算法
本文提出了一种基于多模态决策融合的数据挖掘算法,主要用于解决多层次、多层次多模态数据的关联关系,该算法结合了统计学、排队研究、机器学习和贝叶斯决策融合等方法,与单模态、单数据、单方法得到的结果相比,本文提出的算法最大程度保留了数据中所包含的信息。并将该算法应用于数值数据和文本数据的分析。该算法可以通过修改数据类型和方法来进一步扩展,从而形成新的方法。
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