Boosting Multimedia Big Data Systems

视频数据被认为是最大的大数据。近年来，我们目睹了以极快的速度产生的巨大数据量。根据思科系统公司的数据，视频数据约占美国互联网数据的80%。此外，YouTube用户每分钟上传的视频片段超过300小时。视频数据除了体积大、速度快之外，其不规则性和模糊性（多样性）也使得传统的技术和系统难以对数据进行比较、理解和标注。在拟议的研究计划中，我们的目标是系统地解决理解多媒体大数据复杂性的挑战；处理可扩展性；在各种解决方案的效率和准确性之间进行权衡；设计并实现多媒体内容的组织、分类、搜索和检索系统。

Video data is considered as biggest big data. We have witnessed gigantic volume of data generated at a very fast speed in recent years. According to Cisco Systems, video data counts for around 80% of the Internet data in United States. Also, YouTube users upload more than 300 hours’ video clips in every minute. Besides the large volume and velocity, the irregularities and ambiguities (variety property) of the video data make it difficult to compare, understand, and annotate the data using traditional technology and systems. In the proposed research program, our objective is to systematically address the challenges in understanding the complexity of multimedia big data; to handle scalability; to make trade-off between efficiency and accuracy of various solutions; and to design and implement systems to organize, classify, search, and retrieve multimedia contents.