期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2014
卷号：9
期号：12
页码：97-106
DOI：10.14257/ijmue.2014.9.12.09
出版社：SERSC
摘要：Discovery and subsequent effective retrieval of useful user generated content depends on proper meta-data annotation implemented on an object such as a title and Keywords. In this study, a simpler unsupervised non graph-based algorithm for extracting keywords is proposed. A novel key phrases chunking approach was adopted; this utilizes words sequences as they appear in the original document. The simple but effective Term frequency-inverse document frequency (tf-idf) weighting scheme was exploited to rank the novelty created key- phrases. Comparing to a similar algorithm that uses three metrics weighting scheme, the tf- idf yielded a precision of 89%.Thus, the application of tf-idf algorithm on YouTube's metadata based keywords shows to be useful approach in its objectivity.
关键词：automatic extraction; Tf-Idf Weighting; Forward Words Pruning; ; Objective ; User generated content
