Big Data Abstraction Through Multiagent Systems

2013 ◽  
pp. 173-183 ◽  
Author(s):  
T. Ravindra Babu ◽  
M. Narasimha Murty ◽  
S. V. Subrahmanya
Keyword(s):  
Big Data ◽  
Multiagent Systems ◽  
Data Abstraction

scholarly journals System approach to organization of lean production

2020 ◽  
Vol 311 ◽  
pp. 02010
Author(s):  
Saida Kuizheva ◽  
Lyudmila Zadorozhnaya ◽  
Sergey Chefranov ◽  
Zarina Gasheva
Keyword(s):  
Big Data ◽  
Multiagent Systems ◽  
System Approach ◽  
Lean Production ◽  
The Self ◽  
Current State ◽  
Organizational Problems

The complex of organizational problems of the process of distribution of lean production is Considered. The analysis of directions, specific measures and tools of formalization of the process of distribution of lean production is carried out. Features of procedures of the analysis of the current state and synthesis of specialized systems of management of process of distribution of lean production in the environment of economic subjects are defined, namely: development and introduction of the self-regulating organizations, technocenoses, multiagent systems, technologies of OLAPcube, Big Data.

Overcoming the challenge of variety: big data abstraction, the next evolution of data management for AAL communication systems

2015 ◽  
Vol 53 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Rui Mao ◽  
Honglong Xu ◽  
Wenbo Wu ◽  
Jianqiang Li ◽  
Yan Li ◽  
...  
Keyword(s):  
Big Data ◽  
Data Management ◽  
Communication Systems ◽  
Data Abstraction

Only Can AI Understand Me?

2021 ◽  
pp. 46-66
Author(s):  
Andrew Stranieri ◽  
Zhaohao Sun
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Context ◽  
Multiagent Systems ◽  
Data Science ◽  
Big Data Analytics ◽  
Repeated Exposure ◽  
Regulatory Agencies ◽  
Human Reasoning ◽  
Moral Culpability

This chapter addresses whether AI can understand me. A framework for regulating AI systems that draws on Strawson's moral philosophy and concepts drawn from jurisprudence and theories on regulation is used. This chapter proposes that, as AI algorithms increasingly draw inferences following repeated exposure to big datasets, they have become more sophisticated and rival human reasoning. Their regulation requires that AI systems have agency and are subject to the rulings of courts. Humans sponsor the AI systems for registration with regulatory agencies. This enables judges to make moral culpability decisions by taking the AI system's explanation into account along with the full social context of the misdemeanor. The proposed approach might facilitate the research and development of intelligent analytics, intelligent big data analytics, multiagent systems, artificial intelligence, and data science.

Sampling Techniques Used in Big-Data Driven Applications

2021 ◽  
Vol 2 (1) ◽  
pp. 17-20
Author(s):  
Ramesh Chandra Poonia ◽  
Santosh R Durugkar
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Weather Conditions ◽  
Data Driven ◽  
Sampling Techniques ◽  
Data Abstraction ◽  
Traffic Intensity ◽  
Next Generation ◽  
Contextual Data ◽  
Driven Systems

Data-driven systems process the data from various sources in multiple applications. Data retrieved from heterogeneous sources need to be available in an aggregate and unique format. This requirement gives rise to the process of the Big-data and proposed next-generation big-data processing systems. There are many applications based on contextual data useful for identifying the traffic intensity, changing users per application, weather conditions etc., and serve as next- generation business-specific systems. In such systems data abstraction and representation are the important tasks & granularity can be applied in the data processing. Granularity will process the data from low granularity to high granularity. Sampling plays an important role in the data processing.

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

When the Sample Is the Population: Big Data

PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  
Big Data
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