Analysis of Ontology Semantic Tagging Method for Semantic Web-Oriented Big Data

Author(s):  
Hongsheng Xu ◽  
Shengli Jiang ◽  
Cong Zheng
2018 ◽  
Vol 10 (4) ◽  
pp. 16
Author(s):  
George Bouchagiar

After having shifted from Web 1.0 to Web 2.0, scientists welcome the advent of Web 3.0, an environment where meaning is added to data. While in the Semantic Web people are no longer users, but part of the emerging applications, producers, subjects and beneficiaries of the Big Data, however, opaque processing of personal data poses tremendous risks and dangers for individuals. Given the new era of Big Data this paper studies firms’ purposes and practices to detect some emerging privacy risks. Moreover, theories that deal with social networks are examined to conclude that, even if people state that they value their privacy, however, they often disclose a huge volume of personal information. Taking into account that today’s European concept of privacy is conceptualized in negative terms this paper also proposes the implementation of trust and loyalty into the privacy concept through flexible fiduciary laws. Furthermore, data portability is discussed to detect its potential as a strategic feature, a key tool that will enhance trust. Finally, further scenarios and proposals are submitted, in our attempt to answer the question whether the European concept of privacy could be re-shaped for the benefit of individuals.


2014 ◽  
Vol 8 (4) ◽  
pp. 192-201 ◽  
Author(s):  
Hongyan Wu ◽  
Atsuko Yamaguchi

2016 ◽  
Vol 29 (5) ◽  
pp. 706-727 ◽  
Author(s):  
Mihalis Giannakis ◽  
Michalis Louis

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.


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