Analysis of Context Vector Machine based System for Multimedia Information Retrieval
Rafeeq1, Ravi Kanth.M2, K. Srujan Raju3
1Md. Rafeeq, Associate Professor, Department of CSE, CMR Technical Campus, Kandlakoya, Medchal Hyderabad (Telangana), India.
2Ravi Kanth.M, Associate Professor, Department of CSE, CMR Technical Campus, Kandlakoya, Medchal Hyderabad (Telangana), India.
3K. Srujan Raju, Professor & Head, Department of CSE, CMR Technical Campus Kandlakoya, Medchal Hyderabad (Telangana), India.
Manuscript received on 14 May 2019 | Revised Manuscript received on 19 May 2019 | Manuscript Published on 23 May 2019 | PP: 2019-2022 | Volume-7 Issue-6S5 April 2019 | Retrieval Number: F13640476S519/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The a lot of computerized media getting to be accessible necessitate that new methodologies are created for recovering, exploring and prescribing the information to clients in a way that responds how we semantically see the substance. The postulation researches approaches to recover and give content for clients the assistance of relevant information. has made sound and video an always available medium. The technological advances have also changed the way music is distributed as it has moved from the physical media over digital distribution of files, like Apple’s itunes store2,to on-demand music delivery through streaming services such as Pandora3 and Spotify4. The delivery of other multimedia data such as speech and video have also become an on-demand service, for instance through streaming services, e.g., the ubiquitous presence of Youtube5 on the Web, as well as podcasting and audio books.
Keywords: Information Retrieval; Context; Context Vector; Document Classification.
Scope of the Article: Information Retrieval