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Journal of the Korean Society for Library and Information Science

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Vol.47 No.3
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Comparing the Use of Semantic Relations between Tags Versus Latent Semantic Analysis for Speech Summarization

Journal of the Korean Society for Library and Information Science / Journal of the Korean Society for Library and Information Science, (P)1225-598X; (E)2982-6292
2013, v.47 no.3, pp.343-361
https://doi.org/10.4275/KSLIS.2013.47.3.343

(2013). Comparing the Use of Semantic Relations between Tags Versus Latent Semantic Analysis for Speech Summarization. Journal of the Korean Society for Library and Information Science, 47(3), 343-361, https://doi.org/10.4275/KSLIS.2013.47.3.343
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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, 일반 스피치 요약, 비디오, 태그의미분석, 확장된 태그, 태그 클러스터, 잠재의미분석, F측정, 강의 자료, 플리커, 유투브, 내재적 평가, Expanded Tags, Latent Semantic Analysis, TED Talks, Flickr Tag Clusters, WordNet

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