International Journal of Emerging Trends & Technology in Computer Science
A Motivation for Recent Innovation & Research
ISSN 2278-6856
www.ijettcs.org

Call for Paper, Published Articles, Indexing Infromation Metadata Based Classification and Analysis of Large Scale Web Videos, Authors : Siddu P Algur, Prashant Bhat, International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), www.ijettcs.org
Volume & Issue no: Volume 4, Issue 3, May - June 2015

Title:
Metadata Based Classification and Analysis of Large Scale Web Videos
Author Name:
Siddu P Algur, Prashant Bhat
Abstract:
Abstract The astonishing growth of videos on the Internet such as YouTube, Yahoo Screen, Face Book etc, organizing videos into categories is of paramount importance for improving user experience and website utilization. In this information age, video information is the rapidly sharing by the people through social media websites such as YouTube, Face Book, yahoo Screen etc. Different categories of web video are shared on social websites and used by the billions of users all over the world. The classification/partitioning of web videos in terms of length of the video, ratings, age of the video, number of comments etc, and analysis of this web video as a unstructured complex data is a challenging task. In this work we propose effective classification model to classify each category of web-videos (Ex- ‘Entertainment’, ‘People and Blogs’, ‘Sports’, ‘News and Politics’, ‘Science and Technology’ etc) based on other web metadata attributes as splitting criteria. An attempt is made to extract metadata from web videos. Based on the extracted metadata, web videos are classified/partitioned into different categories by applying data mining classification algorithms such as and Random Tree and J48 classification model. The classification results are compared and analyzed using cost/benefit analysis. Also the results demonstrate classification of web videos depends largely on available metadata and accuracy of the classification model. Classification/partitioning of web-based videos are important task with many applications in video search and information retrieval process. However, collecting metadata required for classification model may be prohibitively expensive. The experimental difficulties arise from large data diversity within a category is pitiable of metadata and dreadful conditions of web video metadata. Keywords: Web Video Mining, Web Video Metadata, Random Tree Algorithm, J48 Algorithm, Web Video Categories.
Cite this article:
Siddu P Algur, Prashant Bhat , " Metadata Based Classification and Analysis of Large Scale Web Videos " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 4, Issue 3, May - June 2015 , pp. 111-120 , ISSN 2278-6856.
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