Big data and collective intelligence

被引:5
作者
Ivanovic, Mirjana [1 ]
Klasnja-Milicevic, Aleksandra [1 ]
机构
[1] Univ Novi Sad, Fac Sci, Dept Math & Informat, Trg D Obradov 4, Novi Sad 21000, Serbia
关键词
big data; big data generation and processing; cloud computing; collective intelligence; artificial intelligence techniques; high performance computing;
D O I
10.1504/IJES.2019.102430
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Nowadays the creation and accumulation of big data is an unavoidable process in a wide range of situations and scenarios. Smart environments and diverse sources of sensors, as well as the content created by humans, contribute to the big data's enormous size and characteristics. To make sense of the data, analyse and use these data, more and more efficient algorithms are being developed constantly. Still, the effectiveness of these algorithms depends on the specific nature of big data: analogue, noisy, implicit, and ambiguous. At the same time, there is the unavoidable scientific area of collective intelligence. It represents the capability of interconnected intelligences to collectively and more efficiently solve concrete problems than each individual intelligence would be able to do on its own. The paper presents an overview of recent achievements in big data and collective intelligence research areas. At the end, the perspectives and challenges of the common directions of these two areas will be discussed.
引用
收藏
页码:573 / 583
页数:11
相关论文
共 39 条
[1]  
Abadi D, 2015, PROC VLDB ENDOW, V8, P2051
[2]   Internet of Things for Smart Cities: Interoperability and Open Data [J].
Ahlgren, Bengt ;
Hidell, Markus ;
Ngai, Edith C. -H. .
IEEE INTERNET COMPUTING, 2016, 20 (06) :52-56
[3]  
[Anonymous], 2014, Inter-Cooperative Collective Intelligence: Techniques and Applications, Studies in Computational Intelligence, DOI DOI 10.1007/978-3-642-35016-0_1
[4]   MIST: Fog-based data analytics scheme with cost-efficient resource provisioning for IoT crowdsensing applications [J].
Arkian, Hamid Reza ;
Diyanat, Abolfazl ;
Pourkhalili, Atefe .
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2017, 82 :152-165
[5]  
Asghari M, 2017, IEEE INT CONF BIG DA, P395, DOI 10.1109/BigData.2017.8257951
[6]  
Bhadani AK, 2016, ADV DATA MIN DATABAS, P1, DOI 10.4018/978-1-5225-0182-4.ch001
[7]  
Bigham J.P., 2010, P 23 ANN ACM S US IN, P333
[8]  
Borne K., 2014, Top 10 Big Data Challenges - A Serious Look at 10 Big Data V's
[9]  
Broadbent S., 2015, Collective intelligence, how does it emerge
[10]   Monitoring and improving performance in human-computer interaction [J].
Carneiro, Davide ;
Pimenta, Andre ;
Goncalves, Sergio ;
Neves, Jose ;
Novais, Paulo .
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2016, 28 (04) :1291-1309