Big data and collective intelligence. (20th September 2019)
- Record Type:
- Journal Article
- Title:
- Big data and collective intelligence. (20th September 2019)
- Main Title:
- Big data and collective intelligence
- Authors:
- Ivanović, Mirjana
Klašnja-Milićević, Aleksandra - Abstract:
- 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.
- Is Part Of:
- International journal of embedded systems. Volume 11:Number 5(2019)
- Journal:
- International journal of embedded systems
- Issue:
- Volume 11:Number 5(2019)
- Issue Display:
- Volume 11, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 11
- Issue:
- 5
- Issue Sort Value:
- 2019-0011-0005-0000
- Page Start:
- 573
- Page End:
- 583
- Publication Date:
- 2019-09-20
- Subjects:
- big data -- big data generation and processing -- cloud computing -- collective intelligence -- artificial intelligence techniques -- cloud computing -- high performance computing
Embedded computer systems -- Periodicals
004.16 - Journal URLs:
- http://www.inderscience.com/ ↗
http://www.inderscience.com/browse/index.php?journalCODE=ijes ↗ - Languages:
- English
- ISSNs:
- 1741-1068
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 11312.xml