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              <text>A classified study on semantic analysis of video summarization</text>
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              <text>Abnormal behavior; Indexing and clustering; Semantics; Sparse dictionary; Video Summarization</text>
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              <text>In today's world data represented in the form of a video are prolific and has increased the requisite of storage devices unconditionally. These video sets takes up a huge space for amassing data and takes a long time to ascertain the content that requires a higher cognitive process for content search and retrieval. The efficient method for storing video data is to remove high-degree redundancies and for creating an index of important events, objects and a preview video based on vital key-frames. These requirements imbibes the need to build algorithms that can concise the necessity of space and time for video and adequate approaches are to be developed to solve the needs of summarization. The three effective attributes for a semantic summarized video system are Un-supervision, efficient and dynamically scalable system that can help in reducing time and space complexities. Dimensionality reduction based on sub space analysis helps in plummeting the multidimensional data into a low-dimensional data to enable faster feature extraction and summarization. In this paper we have made a study and description related to several summarization methodologies for video's that are available.  2017 IEEE.</text>
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          <name>Creator</name>
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              <text>Moses T.M.; Balachandran K.</text>
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              <text>2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies, ICAMMAET 2017, Vol-2017-January, pp. 1-6.</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICAMMAET.2017.8186684" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICAMMAET.2017.8186684&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045834377&amp;amp;doi=10.1109%2FICAMMAET.2017.8186684&amp;amp;partnerID=40&amp;amp;md5=34bc69c7ffbb699f63ba7fadf55a545b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045834377&amp;amp;doi=10.1109%2fICAMMAET.2017.8186684&amp;amp;partnerID=40&amp;amp;md5=34bc69c7ffbb699f63ba7fadf55a545b&lt;/a&gt;</text>
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              <text>ISBN: 978-150903378-2</text>
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              <text>Online</text>
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              <text>Moses T.M., Computer Science and Engineering, Faculty of Engineering, Christ University, Bengaluru, India; Balachandran K., Computer Science and Engineering, Faculty of Engineering, Christ University, Bengaluru, India</text>
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