摘要
随着数字技术的发展和数字化产品的广泛应用，多媒体数据的增长速度明显加快，使得如何从海量的多媒体数据中提取有用的信息引起了广泛的关注。数据挖掘技术作为一种发现隐藏在大量数据背后的潜在模式和有用信息的工具，受到了越来越多的关注。本文针对面向多媒体数据的数据挖掘算法研究与应用进行具体探讨。首先，本文介绍了多媒体数据挖掘的概念、分类和特点。再次，本文介绍了不同的数据挖掘算法，包括关联规则挖掘、分类算法、聚类算法和异常检测算法，并对其原理进行简单描述。然后，本文对基于图像、视频和音频数据的挖掘算法进行了详细的研究。在图像和视频数据的挖掘算法研究方面，本文分别介绍了基于特征的分割算法、基于深度学习的视觉目标检测算法和基于时间序列模型的视频内容建模算法；在音频数据的挖掘算法研究方面，本文介绍了基于频域特征的音乐情感分类算法、基于时频分析的语音情感分类算法和基于卷积神经网络的声音分类算法。最后，本文详细探讨了多媒体数据挖掘的应用，包括多媒体数据检索、多媒体数据分类、多媒体数据聚类和多媒体数据异常检测，并且对其在实际应用中的具体场景进行了分析，为多媒体数据的挖掘提供了一定的启发和参考。
[关键词] 多媒体 数据挖掘 算法 应用
Abstract
With the development of digital technology and the widespread application of digital products, the growth rate of multimedia data has significantly accelerated, causing widespread attention to how to extract useful information from massive multimedia data. Data mining technology, as a tool for discovering potential patterns and useful information hidden behind a large amount of data, has received increasing attention. This article specifically explores the research and application of data mining algorithms for multimedia data. Firstly, this article introduces the concept, classification, and characteristics of multimedia data mining. Once again, this article introduces different data mining algorithms, including association rule mining, classification algorithms, clustering algorithms, and anomaly detection algorithms, and briefly describes their principles. Then, this article conducted a detailed study on mining algorithms based on image, video, and audio data. In terms of mining algorithms for image and video data, this article introduces feature based segmentation algorithms, deep learning based visual ob ject detection algorithms, and time series model based video content modeling algorithms; In terms of research on audio data mining algorithms, this article introduces music sentiment classification algorithms based on frequency domain features, speech sentiment classification algorithms based on time-frequency analysis, and voice classification algorithms based on convolutional neural networks. Finally, this paper discusses the application of multimedia data mining in detail, including multimedia data retrieval, multimedia data classification, multimedia cluster analysis and multimedia data anomaly detection, and analyzes its specific scenarios in practical applications, providing some inspiration and reference for multimedia data mining.
Key words: Multi-Media Data mining Algorithm Application
目 录
摘要 I
Abstract II
引言 1
1 多媒体数据挖掘概述 1
1.1多媒体数据挖掘的概念 1
1.2多媒体数据挖掘的分类 2
1.3多媒体数据挖掘的特点 2
2 多媒体数据处理技术及数据挖掘算法 3
2.1多媒体数据处理技术 3
2.2数据挖掘算法 3
3 基于多媒体数据的挖掘算法研究 4
3.1图像/视频数据挖掘算法研究 4
3.2音频数据挖掘算法研究 4
4 多媒体数据挖掘的应用 5
4.1多媒体数据检索 5
4.2多媒体数据分类 5
4.3多媒体数据聚类 6
4.4多媒体数据异常检测 6
结论 7
参考文献 9
致谢 9
随着数字技术的发展和数字化产品的广泛应用，多媒体数据的增长速度明显加快，使得如何从海量的多媒体数据中提取有用的信息引起了广泛的关注。数据挖掘技术作为一种发现隐藏在大量数据背后的潜在模式和有用信息的工具，受到了越来越多的关注。本文针对面向多媒体数据的数据挖掘算法研究与应用进行具体探讨。首先，本文介绍了多媒体数据挖掘的概念、分类和特点。再次，本文介绍了不同的数据挖掘算法，包括关联规则挖掘、分类算法、聚类算法和异常检测算法，并对其原理进行简单描述。然后，本文对基于图像、视频和音频数据的挖掘算法进行了详细的研究。在图像和视频数据的挖掘算法研究方面，本文分别介绍了基于特征的分割算法、基于深度学习的视觉目标检测算法和基于时间序列模型的视频内容建模算法；在音频数据的挖掘算法研究方面，本文介绍了基于频域特征的音乐情感分类算法、基于时频分析的语音情感分类算法和基于卷积神经网络的声音分类算法。最后，本文详细探讨了多媒体数据挖掘的应用，包括多媒体数据检索、多媒体数据分类、多媒体数据聚类和多媒体数据异常检测，并且对其在实际应用中的具体场景进行了分析，为多媒体数据的挖掘提供了一定的启发和参考。
[关键词] 多媒体 数据挖掘 算法 应用
Abstract
With the development of digital technology and the widespread application of digital products, the growth rate of multimedia data has significantly accelerated, causing widespread attention to how to extract useful information from massive multimedia data. Data mining technology, as a tool for discovering potential patterns and useful information hidden behind a large amount of data, has received increasing attention. This article specifically explores the research and application of data mining algorithms for multimedia data. Firstly, this article introduces the concept, classification, and characteristics of multimedia data mining. Once again, this article introduces different data mining algorithms, including association rule mining, classification algorithms, clustering algorithms, and anomaly detection algorithms, and briefly describes their principles. Then, this article conducted a detailed study on mining algorithms based on image, video, and audio data. In terms of mining algorithms for image and video data, this article introduces feature based segmentation algorithms, deep learning based visual ob ject detection algorithms, and time series model based video content modeling algorithms; In terms of research on audio data mining algorithms, this article introduces music sentiment classification algorithms based on frequency domain features, speech sentiment classification algorithms based on time-frequency analysis, and voice classification algorithms based on convolutional neural networks. Finally, this paper discusses the application of multimedia data mining in detail, including multimedia data retrieval, multimedia data classification, multimedia cluster analysis and multimedia data anomaly detection, and analyzes its specific scenarios in practical applications, providing some inspiration and reference for multimedia data mining.
Key words: Multi-Media Data mining Algorithm Application
目 录
摘要 I
Abstract II
引言 1
1 多媒体数据挖掘概述 1
1.1多媒体数据挖掘的概念 1
1.2多媒体数据挖掘的分类 2
1.3多媒体数据挖掘的特点 2
2 多媒体数据处理技术及数据挖掘算法 3
2.1多媒体数据处理技术 3
2.2数据挖掘算法 3
3 基于多媒体数据的挖掘算法研究 4
3.1图像/视频数据挖掘算法研究 4
3.2音频数据挖掘算法研究 4
4 多媒体数据挖掘的应用 5
4.1多媒体数据检索 5
4.2多媒体数据分类 5
4.3多媒体数据聚类 6
4.4多媒体数据异常检测 6
结论 7
参考文献 9
致谢 9
