Big data recommender systems
by Khalid, Osman Khan, Samee Ullah Zomaya, Albert Y.
The increase in the volumes of data creates new challenges that require novel and more efficient solutions to handle big data and scalability issues. Today we are witnessing advances in many areas that are dependent on recommender systems such as social networks, e-commerce websites, search engines, blogs, and sensor networks. Many of these advances are due to the many developments in algorithmics and analytics, wireless networking, Internet of things, high performance computing, and more. Volu…
Read More ↓Title Statements
- Full title :Big data recommender systems. / edited by Osman Khalid, Samee U. Khan and Albert Y. Zomaya.
Summary
The increase in the volumes of data creates new challenges that require novel and more efficient solutions to handle big data and scalability issues. Today we are witnessing advances in many areas that are dependent on recommender systems such as social networks, e-commerce websites, search engines, blogs, and sensor networks. Many of these advances are due to the many developments in algorithmics and analytics, wireless networking, Internet of things, high performance computing, and more. Volume 2, Big Data Recommender Systems: Application Paradigms, presents a good overview of the many applications that show the richness of this field and its great potential.
Read More ↓Edition Statements
- Publication Date:©2019
Publication Statements
- Publisher(s):IET
- Place of Publication:Stevenage
- Language:eng
- Publication Date:©2019
The Physical Object
- Description:1 online resource (536 pages)
Edition Identifiers
- ISBN:9781785619786, 1785619780, 1523127252, 9781523127252
- oclc:on1112090692
- LC Classification:ZA3084
- Dewey Decimal:005.7
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