Abstract
Nowadays, many applications with massive amount of data caused limitation in data storage capacity and processing time. Traditional data mining is not suitable for this kind of application, so they should be tuned and changed or designed with new algorithms. With the advance technology of multimedia and networking, the digital video contents are widely available over the Web. Thus, it is growing in a faster manner for a wide usage of multimedia applications. It can be downloaded and played using various devices such as cell phones, palms, and laptops with networking technologies such as Wi-Fi, HSDPA, UMTS, and EDGE. The successive Web sites such as Google Video, YouTube, and iTunes are used to download/upload the videos. In such a scenario, a tool would be really required for performing video browsing. Recently, many applications are created for categorizing, indexing, and retrieving the digital video contents. These applications are used to handle large quantity of video contents. The proposed method facilitates the discovery of natural and homogeneous clusters.
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Saravanan, D., Srinivasan, S. (2015). Video Data Mining Information Retrieval Using BIRCH Clustering Technique. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 325. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2135-7_62
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DOI: https://doi.org/10.1007/978-81-322-2135-7_62
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