Multimedia data mining: state of the art and challenges

Advances in multimedia data acquisition and storage technology have led to the growth of very large multimedia databases. Analyzing this huge amount of multimedia data to discover useful knowledge is a challenging problem. This challenge has opened the opportunity for research in Multimedia Data Mining (MDM). Multimedia data mining can be defined as the process of finding interesting patterns from media data such as audio, video, image and text that are not ordinarily accessible by basic queries and associated results. The motivation for doing MDM is to use the discovered patterns to improve decision making. MDM has therefore attracted significant research efforts in developing methods and tools to organize, manage, search and perform domain specific tasks for data from domains such as surveillance, meetings, broadcast news, sports, archives, movies, medical data, as well as personal and online media collections. This paper presents a survey on the problems and solutions in Multimedia Data Mining, approached from the following angles: feature extraction, transformation and representation techniques, data mining techniques, and current multimedia data mining systems in various application domains. We discuss main aspects of feature extraction, transformation and representation techniques. These aspects are: level of feature extraction, feature fusion, features synchronization, feature correlation discovery and accurate representation of multimedia data. Comparison of MDM techniques with state of the art video processing, audio processing and image processing techniques is also provided. Similarly, we compare MDM techniques with the state of the art data mining techniques involving clustering, classification, sequence pattern mining, association rule mining and visualization. We review current multimedia data mining systems in detail, grouping them according to problem formulations and approaches. The review includes supervised and unsupervised discovery of events and actions from one or more continuous sequences. We also do a detailed analysis to understand what has been achieved and what are the remaining gaps where future research efforts could be focussed. We then conclude this survey with a look at open research directions.     

Numerical analysis of catalytic efficiency of diesel exhaust purification based on multimedia aided regression model

Automotive diesel has become an international trend, and more and more attention has been paid to the purification of diesel engine. In the face of the European emission standards, we need to develop emission control technologies applicable to high standards. Outside purification is the key to this technology. In this paper, the technology of diesel engine purification outside and outside of China is analyzed. The principle, characteristics, treatment effect and application prospect of various methods are analyzed. In this paper, the process and influence of the tail gas production in diesel engine fuel combustion are expounded. The chemical characteristics and chemical reaction equations of harmful tail gas, the emission hazard of diesel engine and the method and significance of exhaust gas treatment are listed. With the continuous development of multimedia technology, multimedia teaching plays a more and more important role in the field of modern teaching. At the same time, multimedia teaching is a breakthrough in the traditional backward teaching mode. Multimedia assisted instruction is widely used all over the world, and it also faces many problems caused by improper use while improving students’ academic achievements. Multimedia assisted and regression models are adopted in this paper.

     

E-government multimedia big data platform for disaster management

Multimedia Tools and Applications - By efficiently managing and utilizing the city’s multimedia big data, 3D analysis and visualization of the city’s multimedia information can be...     

Intelligent computational techniques for multimodal data

This guest editorial introduces the special issue on “Intelligent Computational Techniques for Multimodal Data”. The goal of this special issue was to solve a variety of real-life problems which have uncertainty, imprecision, vagueness, resulting in high performance applications or prototypes for real time system. The special issue touched different hot topics related to Computer Vision, Computational Biology, Multimedia data mining, High-dimensional multimedia data, Deep convolution network, Deep semantic preserving hashing, High-dimensional multimedia classification, Deep CNN and extended residual units, particle swarm optimization, Cyberbullying detection on social multimedia, Multimedia detection algorithm of malicious nodes, Multimedia based fast face recognition, Diversifying personalized mobile multimedia application, Multimedia image edge extraction algorithm, Rumour veracity detection.

     

开滦集团全息数字化矿山管理平台的研究与设计

全息数字化矿山管理平台依托3D-GIS技术和虚拟仿真技术,通过构建一体化的三维可视化平台,将矿山地形地貌、地表设施、井巷工程、矿体围岩等客观空间构造,在平台系统中真实再现,充分利用现代空间分析、数据采矿、知识挖掘、虚拟现实、可视化、网络、多媒体和科学计算技术,为矿产资源评估、矿山规划、开拓设计、生产安全和决策管理进行模拟、仿真和过程分析提供新的技术平台和强大工具。     

Image information loss estimation of video stream based on improved SPIHT algorithm

Multimedia Tools and Applications - With the continuous development of multimedia technology, digital image and video data show a massive growth. Many files containing image and video data often...     

煤矿地质三维可视化的研究与应用

利用SQL Server 2005为数据库,采用先进的TIN数字高程模型、VC＋＋面向对象技术和多媒体建模方法作为前台开发工具,利用不规则三角网Delaunay算法自动生成标准的TIN三角网地形,通过OpenGL强大的三维处理和显示引擎,实时、动态生成各种矿井实体,再现井上下真实的三维场景,构建三维可视化应用,实现了煤矿三维可视化系统。     

基于局域网的多媒体电子教室系统开发技术

多媒体电子教室系统是一种信息化教学的多媒体技术平台。它结合了传统的课堂教学方法与多媒体技术和计算机交互技术,使更多的课堂教学方法得到优化。使用多媒体教学系统,教师可以根据教学内容,教学进度,教学效果和学生的特点有效的融合起来。     

Feature selection in multimedia: The state-of-the-art review

Multimedia data mining, particularly feature selection (FS), has been successfully applied in recent classification and recognition works. However, only a few studies in the contemporary literature have reviewed FS (e.g., analyses of data pre-processing prior to classification and clustering). This study aimed to fill this research gap by presenting an extensive survey on the current development of FS in multimedia. A total of 70 related papers published from 2001 to 2017 were collected from multiple databases. Breakdowns and analyses were performed on data types, methods, search strategies, performance measures, and challenges. The development trend of FS presages the increased prominence of heuristic search strategies and hybrid FS in the latest multimedia data mining.     

加强多媒体教学设备安全运行管理的措施探讨

随着我国教育事业的发展,教育部开始大力实施教育信息化建设工程,各中小学及高校开始普及多媒体教学。多媒体教学彻底改变了传统的教学方式,以图像、动画及视频等为载体,代表着信息科技的发展;加强多媒体教学设备的安全运行管理则显得尤为重要,本文首先对一种基于非接触式IC卡的智能安全管理系统进行了研究,对具体的设计方法进行了分析,随后对多媒体教学设备的安全管理与维护进行了阐述,以期给相关人员参考。     

空间数据可视化的研究与发展

随着3S技术的融合和空间信息处理技术的发展和广泛应用,空间数据的可视化以及基于可视化技术的空间分析、空间数据挖掘和知识发现已经发展成为空间信息处理的重要手段和关键技术。可视化方法已由数据的空间展现逐步发展成为可以表现数据的内在复杂结构、关系和规律的技术。由静态空间关系的可视化发展到表示系统演变过程的可视化。可视化方法不仅用于数据的理解,而且用于空间知识的呈现。可视化技术充分利用了人对于色彩和空间的敏锐的感知能力使人机有机地融合,在空间信息和知识的发现过程中发挥着重要作用。该文总结了空间分析中可视化技术的研究成果,分析了可视化技术的发展现状,给出了可视化方法的分类。从认知和空间数据所表征的客观对象的复杂性及非线性动力学特征分析了其发展演化规律的可视化方法,并对空间数据可视化技术的现状及发展趋势进行探讨。     

Design and evaluation of visualization support to facilitate association rules modeling

Association rules mining is a popular data mining modeling tool. It discovers interesting associations or correlation relationships among a large set of data items, showing attribute values that occur frequently together in a given dataset. Despite their great potential benefit, current association rules modeling tools are far from optimal. This article studies how visualization techniques can be applied to facilitate the association rules modeling process, particularly what visualization elements should be incorporated and how they can be displayed. Original designs for visualization of rules, integration of data and rule visualizations, and visualization of rule derivation process for supporting interactive visual association rules modeling are proposed in this research. Experimental results indicated that, compared to an automatic association rules modeling process, the proposed interactive visual association rules modeling can significantly improve the effectiveness of modeling, enhance understanding of the applied algorithm, and bring users greater satisfaction with the task. The proposed integration of data and rule visualizations can significantly facilitate understanding rules compared to their nonintegrated counterpart.     

构建地球科学研究的时空数据平台

在统一的数据标准和规范下,系统集成了中国陆地表层的自然要素的空间数据库群及人口和社会经济空间数据库及其元数据库。研究空间数据集成的尺度效应与尺度转换、空间数据挖掘的算法与工具等关键技术。为地球陆地表层过程的基础研究提供了时空数据平台,为海量的资源环境时空数据共享提供了技术上的支持。     

面向海洋的多模态智能计算：挑战、进展和展望

海洋是高质量发展的要地,海洋科学大数据的发展为认知和经略海洋带来机遇的同时也引入了新的挑战。海洋科学大数据具有超多模态的显著特征,目前尚未形成面向海洋领域特色的多模态智能计算理论体系和技术框架。因此,本文首次从多模态数据技术的视角,系统性介绍面向海洋现象/过程的智能感知、认知和预知的交叉研究进展。首先,通过梳理海洋科学大数据全生命周期的阶段演进过程,明确海洋多模态智能计算的研究对象、科学问题和典型应用场景。其次,在海洋多模态大数据内容分析、推理预测和高性能计算3个典型应用场景中展开现有工作的系统性梳理和介绍。最后,针对海洋数据分布和计算模式的差异性,提出海洋多模态大数据表征建模、跨模态关联、推理预测以及高性能计算4个关键科学问题中的挑战,并提出未来展望。     

Learning Based Neural Similarity Metrics for Multimedia Data Mining

Multimedia data mining refers to pattern discovery, rule extraction and knowledge acquisition from multimedia database. Two typical tasks in multimedia data mining are of visual data classification and clustering in terms of semantics. Usually performance of such classification or clustering systems may not be favorable due to the use of low-level features for image representation, and also some improper similarity metrics for measuring the closeness between multimedia objects as well. This paper considers a problem of modeling similarity for semantic image clustering. A collection of semantic images and feed-forward neural networks are used to approximate a characteristic function of equivalence classes, which is termed as a learning pseudo metric (LPM). Empirical criteria on evaluating the goodness of the LPM are established. A LPM based k-Mean rule is then employed for the semantic image clustering practice, where two impurity indices, classification performance and robustness are used for performance evaluation. An artificial image database with 11 semantics is employed for our simulation studies. Results demonstrate the merits and usefulness of our proposed techniques for multimedia data mining.     

教育大数据可视化研究综述

教育大数据可视化分析对于复杂教育规律的理解与挖掘具有重要作用,已成为当前教育信息科学研究领域的重要课题。首先归纳了教育大数据的典型特征,从促进学生元认知发展、辅助教师监督学习过程及提升管理者科学决策水平三个角度介绍了教育大数据应用的最新研究成果,并简述了利用教育大数据实施可视化分析的基本流程。然后重点对文本数据可视化、多维数据可视化、网络数据可视化、时间序列数据可视化以及地理空间数据可视化等五种主流的教育大数据可视化呈现方法进行特征描述,并给出具体的应用场景。随后介绍了动态查询与过滤技术、可缩放/变形界面技术和多视图联动技术三个实施教育大数据可视化的关键交互技术方法。最后依据最新研究动态,从多模态教育数据融合、人机交互、人机协同范式以及教育数据可视化设计的标准规范和评价体系四方面对教育大数据可视化未来研究方向进行了展望。     

多媒体技术研究：2012——多媒体数据索引与检索技术研究进展

随着计算机网络、社交媒体、数字电视和多媒体获取设备的快速发展, 多媒体数据的生成、处理和获取变得越来越方便, 多媒体应用日益广泛, 数据量呈现出爆炸性的增长, 已经成为大数据时代的主要数据对象。然而由于多媒体数据本身的非结构化特性, 使得多媒体数据的处理和检索相对困难。如何有效地存储、组织和管理这些数据, 如何有效地按照多媒体的内容和特性去存取和检索这些数据, 已经成为一种迫切的需求。面向大数据时代多媒体数据的索引和检索问题, 围绕视频事件检测和标注、高维索引结构、跨媒体搜索3个研究方向, 系统阐述了2012年度的技术发展状况, 并对未来的发展趋势进行展望。     

多媒体教学录播与编辑系统的开发

随着科学技术的飞速发展,多媒体教学录播与编辑系统技术也取得了飞跃性的进步。多媒体教学录播与编辑系统同时也在远程教学中得到了广泛的应用,该技术提供的音频视频教学课件使学习实现了网络化,生动的情景再现为异域地学子的求学提供了坚实的技术支持。     

多媒体教学的几点思考

以计算机为核心的多媒体教学方式,集声音、图画、文字、动画等多种感觉于一体,具有直观的图像、鲜明的色彩、逼真的音响、动静结合、形象生动的特点。这一教学手段,有利于更好的培养学生的学习兴趣。多媒体教学技术的应用及发展,必将对教育产生深远的影响。