Solving Conflicts in Video Semantic Annotation Using Consensus-Based Social Networking in a Smart TV Environment

Duong, Thuc‐Huy; Dao, Tran Hoang Chau; Jung, Jason J.; Nguyên, Ngoc Thanh

doi:10.1007/978-3-319-06569-4_15

Cited by 1 publication

(3 citation statements)

References 29 publications

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“…The problem has also been an active area of research, where many work have been published in the literature. But there are several reasons why video content can be difficult to indexing, searching and retrieval effectively, despite noteworthy works 187 . The first is that the multimedia semantics domain is unlimited.…”

Section: Semantic Analysis In Social Networkmentioning

confidence: 99%

“…As a result, the need for a system to allow effective manipulation of video content has been undeniable. The study 187 proposed a collaborative semantic video annotation framework using a social network based on consensus. In the study, two kinds of ontologies were used to define media content semantically and to facilitate the sharing of media content among heterogeneous users or devices.…”

Section: Semantic Analysis In Social Networkmentioning

confidence: 99%

“…But there are several reasons why video content can be difficult to indexing, searching and retrieval effectively, despite noteworthy works. 187 The first is that the multimedia semantics domain is unlimited. Namely, we cannot effectively describe rich multimedia objects that contain video in a few words.…”

Section: Semantic Video Analysismentioning

confidence: 99%

See 2 more Smart Citations

Semantic analysis on social networks: A survey

Bayrakdar

Yücedağ

Şimşek

et al. 2020

Int J Communication

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Summary As social networks are getting more and more popular day by day, large numbers of users becoming constantly active social network users. In this way, there is a huge amount of data produced by users in social networks. While social networking sites and dynamic applications of these sites are actively used by people, social network analysis is also receiving an increasing interest. Moreover, semantic understanding of text, image, and video shared in a social network has been a significant topic in the network analysis research. To the best of the author's knowledge, there has not been any comprehensive survey of social networks, including semantic analysis. In this survey, we have reviewed over 200 contributions in the field, most of which appeared in recent years. This paper not only aims to provide a comprehensive survey of the research and application of social network analysis based on semantic analysis but also summarizes the state‐of‐the‐art techniques for analyzing social media data. First of all, in this paper, social networks, basic concepts, and components related to social network analysis were examined. Second, semantic analysis methods for text, image, and video in social networks are explained, and various studies about these topics are examined in the literature. Then, the emerging approaches in social network analysis research, especially in semantic social network analysis, are discussed. Finally, the trending topics and applications for future directions of the research are emphasized; the information on what kind of studies may be realized in this area is given.

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Section: Semantic Analysis In Social Networkmentioning

confidence: 99%

Section: Semantic Analysis In Social Networkmentioning

confidence: 99%