A collaborative algorithm for semantic video annotation using a consensus-based social network analysis

Duong, Thuc‐Huy; Nguyên, Ngoc Thanh; Truong, Hai Bang; Nguyen, Van Huan

doi:10.1016/j.eswa.2014.07.046

Cited by 19 publications

(3 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [42] a consensus-based model based on SNA has been defined to reconcile conflicts in the collaborative annotation of media content. In [9] SNA metrics are used for the first time to estimate social influence between experts.…”

Section: Social Influence and Opinion Changementioning

confidence: 99%

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Capuano

Chiclana

Fujita

et al. 2018

IEEE Trans. Fuzzy Syst.

279

106

View full text Add to dashboard Cite

A promising research area in the field of Group Decision Making (GDM) is the study of interpersonal influence and its impact on the evolution of experts' opinions. In conventional GDM models, a group of experts express their individual preferences on a finite set of alternatives, then preferences are aggregated and the best alternative, satisfying the majority of experts, is selected. Nevertheless, in real situations, experts form their opinions in a complex interpersonal environment where preferences are liable to change due to social influence. In order to take into account the effects of social influence during the GDM process, we propose a new influence-guided GDM model based on the following assumptions: experts influence each other and the more an expert trusts in another expert, the more his opinion is influenced by that expert. The effects of social influence are especially relevant to cases when, due to domain complexity, limited expertise or pressure to make a decision, an expert is unable to express preferences on some alternatives, i.e. in presence of incomplete information. The proposed model adopts fuzzy rankings to collect both experts' preferences on available alternatives and trust statements on other experts. Starting from collected information, possibly incomplete, the configuration and the strengths of interpersonal influences are evaluated and represented through a Social Influence Network (SIN). The SIN, in its turn, is used to estimate missing preferences and evolve them by simulating the effects of experts' interpersonal influence before aggregating them for the selection of the best alternative. The proposed model has been experimented with synthetic data to demonstrate the influence driven evolution of opinions and its convergence properties.

show abstract

Section: Social Influence and Opinion Changementioning

confidence: 99%

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Capuano

Chiclana

Fujita

et al. 2018

IEEE Trans. Fuzzy Syst.

279

106

View full text Add to dashboard Cite

show abstract

“…A wildfires characteristics will naturally shift as time goes on. Second, semantic annotation, the transformation of raw data into human-understandable information, has achieved great progress (Duong et al, 2015). In this paradigm, different views of the same data stream are constructed from various sources of information, such as spatial information, domain knowledge, and environmental information.…”

Section: Introductionmentioning

confidence: 99%

Real-time wildfire detection with semantic explanations

Phan¹,

Quach²,

Nguyen³

et al. 2022

Expert Systems with Applications

View full text Add to dashboard Cite

“…Both standards provide excellent way to create and deploy an infrastructure for the Web 2.0. The Semantic Web provides annotating document using semantic information from standard model for data interchange on the Web 10–12 . Indeed, the Open Annotation Collaboration (OAC) is proposed as a W3C framework for annotation in the Semantic Web context.…”

Section: Introductionmentioning

confidence: 99%

A conflict‐free replicated data type for collaborative annotation systems

Zarzour

Jararweh

2020

Concurrency and Computation

View full text Add to dashboard Cite

With the advent of Web 2.0, numerous collaborative annotation systems have been developed in an effort to enable distant users to annotate the same multimedia resources such as texts, audio, images, and videos. However, the existing systems do not support the semantic aspect of the data available on the Web and ignore the convergence aspect when executing concurrent annotations. Based on the technologies of Semantic Web, this article presents a new conflict-free replicated data type called OAC-Set, which extends Open Annotation Collaboration data model to enable concurrent annotations while guaranteeing convergence, causality, and intention preservation criteria. The experimental results show that our approach is efficient and effective.

show abstract

A collaborative algorithm for semantic video annotation using a consensus-based social network analysis

Cited by 19 publications

References 19 publications

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Fuzzy Group Decision Making With Incomplete Information Guided by Social Influence

Real-time wildfire detection with semantic explanations

A conflict‐free replicated data type for collaborative annotation systems

Contact Info

Product

Resources

About