About: Time-sync Video Tag Extraction Using Semantic Association Graph

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Time-sync Video Tag Extraction Using Semantic Association Graph
Creator	Zhao, Wei Liu, Nan Gao, Wenyuan Wang, Kun Jia, Weijia Ruan, N Ruan, Na Yang, Wenmain Zhang, Yunyong
Source	ArXiv
abstract	Time-sync comments reveal a new way of extracting the online video tags. However, such time-sync comments have lots of noises due to users' diverse comments, introducing great challenges for accurate and fast video tag extractions. In this paper, we propose an unsupervised video tag extraction algorithm named Semantic Weight-Inverse Document Frequency (SW-IDF). Specifically, we first generate corresponding semantic association graph (SAG) using semantic similarities and timestamps of the time-sync comments. Second, we propose two graph cluster algorithms, i.e., dialogue-based algorithm and topic center-based algorithm, to deal with the videos with different density of comments. Third, we design a graph iteration algorithm to assign the weight to each comment based on the degrees of the clustered subgraphs, which can differentiate the meaningful comments from the noises. Finally, we gain the weight of each word by combining Semantic Weight (SW) and Inverse Document Frequency (IDF). In this way, the video tags are extracted automatically in an unsupervised way. Extensive experiments have shown that SW-IDF (dialogue-based algorithm) achieves 0.4210 F1-score and 0.4932 MAP (Mean Average Precision) in high-density comments, 0.4267 F1-score and 0.3623 MAP in low-density comments; while SW-IDF (topic center-based algorithm) achieves 0.4444 F1-score and 0.5122 MAP in high-density comments, 0.4207 F1-score and 0.3522 MAP in low-density comments. It has a better performance than the state-of-the-art unsupervised algorithms in both F1-score and MAP.
has issue date	2019-05-03(xsd:dateTime)
bibo:doi	10.1145/3332932
has license	arxiv
sha1sum (hex)	1ca24bd4e9b69abe697e3c947bc3cd61da1513cd
schema:url	https://doi.org/10.1145/3332932
resource representing a document's title	Time-sync Video Tag Extraction Using Semantic Association Graph
resource representing a document's body	covid:1ca24bd4e9b69abe697e3c947bc3cd61da1513cd#body_text
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