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http://dx.doi.org/10.4275/KSLIS.2013.47.3.343

Comparing the Use of Semantic Relations between Tags Versus Latent Semantic Analysis for Speech Summarization  

Kim, Hyun-Hee (명지대학교 문헌정보학과)
Publication Information
Journal of the Korean Society for Library and Information Science / v.47, no.3, 2013 , pp. 343-361 More about this Journal
Abstract
We proposed and evaluated a tag semantic analysis method in which original tags are expanded and the semantic relations between original or expanded tags are used to extract key sentences from lecture speech transcripts. To do that, we first investigated how useful Flickr tag clusters and WordNet synonyms are for expanding tags and for detecting the semantic relations between tags. Then, to evaluate our proposed method, we compared it with a latent semantic analysis (LSA) method. As a result, we found that Flick tag clusters are more effective than WordNet synonyms and that the F measure mean (0.27) of the tag semantic analysis method is higher than that of LSA method (0.22).
Keywords
Expanded Tags; Latent Semantic Analysis; TED Talks; Flickr Tag Clusters; WordNet;
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Times Cited By KSCI : 2  (Citation Analysis)
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