Semantic based representing and organizing surveillance big data using video structural description technology

Xu, Zheng; Liu, Yunhuai; Mei, Lin; Hu, Chuanping; Chen, Lan

doi:10.1016/j.jss.2014.07.024

Cited by 113 publications

(34 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work is based on a multilayered security paradigm that can protect data in real time at the following security layers: firewall and access control, identity management, intrusion prevention, and convergent encryption. Another work that targets real-time content is presented in [10], in which a semantic-based video organizing platform is proposed to search videos in big data volumes. The proposed technique uses a semantic relational network model to mine and organize video resources based on their associations, while the authors in [11] proposed a Dynamic Key Length based Security Framework (DLSeF) founded on a common key resulting from synchronized prime numbers.…”

Section: Related Workmentioning

confidence: 99%

An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

Alouneh

Al‐Hawari

Hababeh

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

The need for effective approaches to handle big data that is characterized by its large volume, different types, and high velocity is vital and hence has recently attracted the attention of several research groups. This is especially the case when traditional data processing techniques and capabilities proved to be insufficient in that regard. Another aspect that is equally important while processing big data is its security, as emphasized in this paper. Accordingly, we propose to process big data in two different tiers. The first tier classifies the data based on its structure and on whether security is required or not. In contrast, the second tier analyzes and processes the data based on volume, variety, and velocity factors. Simulation results demonstrated that using classification feedback from a MPLS/GMPLS core network proved to be key in reducing the data evaluation and processing time.

show abstract

Section: Related Workmentioning

confidence: 99%

An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

Alouneh

Al‐Hawari

Hababeh

et al. 2018

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

“…The limitation of their approach is that the ontology proposed by them is too general and is lack of reasoning ability among multiple products. In [7], a whole framework for building domain ontology of video is proposed. The semantic link network model is used to mine and organize video resources based on their associations.…”

Section: Ontology Descriptionmentioning

confidence: 99%

Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining

Wan

Liu

2016

International Conferences on Software Engineering and Knowledge Engineering

View full text Add to dashboard Cite

Abstract-With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g., reviews, forum discussions, blogs, microblogs, comments, and postings in social network sites) for decision making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis results. Ontology provides knowledge about specific domains that are understandable by both the computers and developers. Building ontology is mainly a useful first step in providing and formalizing the semantics of information representation. We proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information. The ontology DEMLOnto would help in identifying the opinion features associated with the contextual environment, which may change along with applications. We built the ontology according to ontology engineering. It was developed on the platform Proté gé by using OWL.

show abstract

“…Is not difficult to see that the conversion of data at multiple scales of the principle is simple, but requires multi-scale forms of data were analyzed, workload is big; knowledge of scaling the workload is small, only a single scale of data analysis, but need to solve the problem of scale effect, complexity theory. Scale effect is the conclusion that a certain scale cannot be applied to another scale [18], that is, when the study object to change its scope of performance, size or amplitude, the analysis results will be changed with [19,20]. Similarly, in a certain scale data focuses on knowledge cannot be no difference in applicable in other scales in the data, we must use domain knowledge or multi-scale data set between relationship of analysis results are deduced, naturalization, is it possible to achieve true knowledge of multi-scale conversion.…”

Section: B the Essence Of Multi-scale Data Analysismentioning

confidence: 99%

Deep Data Anaylizing Method Based on Scale Space Theory

Hu¹,

Chen²,

Gao³

2016

International Conferences on Software Engineering and Knowledge Engineering

View full text Add to dashboard Cite

Abstract-Scale space theory has been introduced into the field of big data, but its research is still not deep enough and perfect because of the lack of universal theory and method. With deepening of big data processing applications, the research becomes more and more urgent. In view of the above question, this paper studies pervasive multi-scale data analysis theory and method. On one hand, we give the definition and partition of data scale as well as the relationship of multi-scale data set between the upper scale and lower scale based on concept hierarchy theory. On the other hand, we clarify the definition of multi-scale data analysis, study essence and classification method. Previous studies show that the proposed method has high coverage rate, high accuracy rate, lower error rate of support estimation degree and greater improvement the efficiency than the traditional algorithm.

show abstract

Semantic based representing and organizing surveillance big data using video structural description technology

Cited by 113 publications

References 37 publications

An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining

Deep Data Anaylizing Method Based on Scale Space Theory

Contact Info

Product

Resources

About