Tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery

Harakawa, Ryosuke; Ogawa, Takahiro; Haseyama, Miki

Tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery

Harakawa, Ryosuke; Ogawa, Takahiro; Haseyama, Miki

Multimedia Tools and Applications, 2018, 77(16), 20297-20324

Permalink : https://hdl.handle.net/2115/75091

このアイテムのアクセス数:581件（2026-08-19 06:26 集計）

閲覧可能ファイル

ファイル	フォーマット	サイズ	閲覧回数	説明
Tracking Topic Evolution via Salient Keyword Matching with Consideration of Semantic Broadness for Web Video Discovery	pdf	1.70 MB	808

論文情報

ファイル出力 EndNote Basic出力 Mendeley出力

アクセス権	open access
URI	https://hdl.handle.net/2115/75091
タイトル	Tracking topic evolution via salient keyword matching with consideration of semantic broadness for Web video discovery
著者	Harakawa, Ryosuke ; Ogawa, Takahiro ; Haseyama, Miki
著者名 Harakawa, Ryosuke
e-Rad_Researcher 20524028 著者名 Ogawa, Takahiro
e-Rad_Researcher 00218463 著者名 Haseyama, Miki
言語	英語
キーワード	Web video
	Video retrieval
	Topic evolution
	Tracking algorithm
	Network analysis
発行日	2018-08
出版者	Springer
収録物名	Multimedia Tools and Applications
巻(号)	77(16)
ページ	20297-20324
抄録	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.
資源タイプ	学術雑誌論文
出版タイプ	Accepted Manuscript
権利情報	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
PISSN	1380-7501
EISSN	1573-7721
NCID	AA11043871
関連情報 (isVersionOf)	出版社版DOI https://doi.org/10.1007/s11042-017-5404-4