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Tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery
| Title: | Tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery |
| Authors: | Harakawa, Ryosuke Browse this author | | Ogawa, Takahiro Browse this author →KAKEN DB | | Haseyama, Miki Browse this author →KAKEN DB |
| Keywords: | Web video | | Video retrieval | | Topic evolution | | Tracking algorithm | | Network analysis |
| Issue Date: | Aug-2018 |
| Publisher: | Springer |
| Journal Title: | Multimedia Tools and Applications |
| Volume: | 77 |
| Issue: | 16 |
| Start Page: | 20297 |
| End Page: | 20324 |
| Publisher DOI: | 10.1007/s11042-017-5404-4 |
| Abstract: | A method to track topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery is presented in this paper. The proposed method enables users to understand the evolution of topics over time for discovering Web videos in which they are interested. A framework that enables extraction and tracking of the hierarchical structure, which contains Web video groups with various degrees of semantic broadness, is newly derived as follows: Based on network analysis using multimodal features, i.e., features of video contents and metadata, our method extracts the hierarchical structure and salient keywords that represent contents of each Web video group. Moreover, salient keyword matching, which is newly developed by considering salient keyword distribution, semantic broadness of each Web video group and initial topic relevance, is applied to each hierarchical structure obtained in different time stamps. Unlike methods in previous works, by considering the semantic broadness as well as the salient keyword distribution, our method can overcome the problem of the desired semantic broadness of topics being different depending on each user. Also, the initial topic relevance enables correction of the gap from an initial topic at the start of tracking. Consequently, it becomes feasible to track the evolution of topics over time for finding Web videos in which the users are interested. Experimental results for real-world datasets containing YouTube videos verify the effectiveness of the proposed method. |
| Rights: | This is a post-peer-review, pre-copyedit version of an article published in "Multimedia Tools and Applications". The final authenticated version is available online at: http://dx.doi.org/10.1007/s11042-017-5404-4 |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/75091 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 原川 良介
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