The amount of information on the world wide web has grown enormously since its creation in 1990. Duplication of content is inevitable because there is no central management on the web. Studies have shown that many similar versions of the same text documents can be found throughout the web. This redundancy problem is more severe for multimedia content such as web video sequences, as they are often stored in multiple locations and different formats to facilitate downloading and streaming. Similar versions of the same video can also be found, unknown to content creators, when web users modify and republish original content using video editing tools. Identifying similar content can benefit many web applications and content owners. For example, it will reduce the number of similar answers to a web search and identify inappropriate use of copyright content. In this dissertation, they present a system architecture and corresponding algorithms to efficiently measure, search, and organize similar video sequences found on any large database such as the web.