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  • × author_ss:"Kim, Y.H."
  • × type_ss:"a"
  1. Kim, H.H.; Kim, Y.H.: Generic speech summarization of transcribed lecture videos : using tags and their semantic relations (2016) 0.01 
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    Abstract
    We propose a tag-based framework that simulates human abstractors' ability to select significant sentences based on key concepts in a sentence as well as the semantic relations between key concepts to create generic summaries of transcribed lecture videos. The proposed extractive summarization method uses tags (viewer- and author-assigned terms) as key concepts. Our method employs Flickr tag clusters and WordNet synonyms to expand tags and detect the semantic relations between tags. This method helps select sentences that have a greater number of semantically related key concepts. To investigate the effectiveness and uniqueness of the proposed method, we compare it with an existing technique, latent semantic analysis (LSA), using intrinsic and extrinsic evaluations. The results of intrinsic evaluation show that the tag-based method is as or more effective than the LSA method. We also observe that in the extrinsic evaluation, the grand mean accuracy score of the tag-based method is higher than that of the LSA method, with a statistically significant difference. Elaborating on our results, we discuss the theoretical and practical implications of our findings for speech video summarization and retrieval.
    Date
    22. 1.2016 12:29:41
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.2, S.366-379
  2. Kim, H.H.; Kim, Y.H.: Toward a conceptual framework of key-frame extraction and storyboard display for video summarization (2010) 0.00 
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    Abstract
    Two key problems in developing a storyboard are (a) the extraction of video key frames and (b) the display of the storyboard. On the basis of our findings from a preliminary study as well as the results of previous studies on the computerized extraction of key frames and human recognition of images and videos, we propose an algorithm for the extraction of key frames and the structural display of a storyboard. In order to evaluate the proposed algorithm, we conducted an experiment, the results of which suggest that participants produce better summaries of the given videos when they view storyboards that are composed of key frames extracted using the proposed algorithmic method. This finding held, regardless of whether the display pattern used was sequential or structural. In contrast, the experimental results suggest that in the case of employing a mechanical method, the use of a structural display pattern yields greater performance in terms of participants' ability to summarize the given videos. Elaborating on our results, we discuss the practical implications of our findings for video summarization and retrieval.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.927-939
  3. Kim, H.H.; Kim, Y.H.: ERP/MMR algorithm for classifying topic-relevant and topic-irrelevant visual shots of documentary videos (2019) 0.00 
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    Footnote
    Beitrag in einem 'Special issue on neuro-information science'.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.9, S.931-941
  4. Kim, Y.H.; Kim, H.H.: Development and validation of evaluation indicators for a consortium of institutional repositories : a case study of dcollection (2008) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 59(2008) no.8, S.1282-1294
  5. Kim, H.H.; Kim, Y.H.: Video summarization using event-related potential responses to shot boundaries in real-time video watching (2019) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.2, S.164-175

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