scholarly journals Fast Access and Retrieval of Big Data Based on Unique Identification

2022 ◽  
Vol 32 (3) ◽  
pp. 1781-1795
Author(s):  
Wenshun Sheng ◽  
Aiping Xu ◽  
Shengli Wu
Keyword(s):  
Big Data ◽  
Author(s):  
Amine Rahmani

The phenomenon of big data (massive data mining) refers to the exponential growth of the volume of data available on the web. This new concept has become widely used in recent years, enabling scalable, efficient, and fast access to data anytime, anywhere, helping the scientific community and companies identify the most subtle behaviors of users. However, big data has its share of the limits of ethical issues and risks that cannot be ignored. Indeed, new risks in terms of privacy are just beginning to be perceived. Sometimes simply annoying, these risks can be really harmful. In the medium term, the issue of privacy could become one of the biggest obstacles to the growth of big data solutions. It is in this context that a great deal of research is under way to enhance security and develop mechanisms for the protection of privacy of users. Although this area is still in its infancy, the list of possibilities continues to grow.


Author(s):  
Amine Rahmani

The phenomenon of big data (massive data mining) refers to the exponential growth of the volume of data available on the web. This new concept has become widely used in recent years, enabling scalable, efficient, and fast access to data anytime, anywhere, helping the scientific community and companies identify the most subtle behaviors of users. However, big data has its share of the limits of ethical issues and risks that cannot be ignored. Indeed, new risks in terms of privacy are just beginning to be perceived. Sometimes simply annoying, these risks can be really harmful. In the medium term, the issue of privacy could become one of the biggest obstacles to the growth of big data solutions. It is in this context that a great deal of research is under way to enhance security and develop mechanisms for the protection of privacy of users. Although this area is still in its infancy, the list of possibilities continues to grow.


2017 ◽  
Vol 13 (6) ◽  
pp. 192-198
Author(s):  
Carlos Roberto Valêncio ◽  
André Francisco Morielo Caetano ◽  
Angelo Cesar Colombini ◽  
Mário Luiz Tronco ◽  
Márcio Zamboti Fortes

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

Find Out About 'Big Data' to Track Outcomes


2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  

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.


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

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


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

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