Clustering Search Results of Non-text User Generated Content

Title
Clustering Search Results of Non-text User Generated Content
Authors
리사김래현
Keywords
User-generated content; Clustering; Recommendation system for UGC
Issue Date
2010-07
Publisher
International Conference on Digital Information Management (ICDIM2010)
Abstract
Non-text user generated content (UGC), such as videos and images, is usually searched by metadata. Metadata, such as title, tags, and description, is created by users whenever content is uploaded. However, in many cases metadata can have multiple meanings. This requires users to spend time sifting through a long list of search results until they can find all the content for which they were actually looking. In order to address this limitation, we suggest an algorithm to cluster search results using keyword similarity. Clustering search results from YouTube are accomplished by using the Markov clustering algorithm, which helps users to quickly and easily find what they want. Finally, we conclude by evaluating the performance results of our clustering algorithm.
URI
http://pubs.kist.re.kr/handle/201004/37951
ISSN
201007
Appears in Collections:
KIST Publication > Conference Paper
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