Recommendation and Search in Social Networks
Nonfiction, Computers, Database Management, General Computing, Social & Cultural Studies, Social Science
| Author: | ISBN: | 9783319143798 | |
| Publisher: | Springer International Publishing | Publication: | February 12, 2015 |
| Imprint: | Springer | Language: | English |
| Author: | |
| ISBN: | 9783319143798 |
| Publisher: | Springer International Publishing |
| Publication: | February 12, 2015 |
| Imprint: | Springer |
| Language: | English |
This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems. Within the broader context of social network analysis it focuses on important and up-coming topics such as real-time event data collection, frequent-sharing pattern mining, improvement of computer-mediated communication, social tagging information, search system personalization, new detection mechanisms for the identification of online user groups, and many more. The twelve contributed chapters are extended versions of conference papers as well as completely new invited chapters in the field of social search and recommendation systems. This first-of-its kind survey of current methods will be of interest to researchers from both academia and industry working in the field of social networks.
This edited volume offers a clear in-depth overview of research covering a variety of issues in social search and recommendation systems. Within the broader context of social network analysis it focuses on important and up-coming topics such as real-time event data collection, frequent-sharing pattern mining, improvement of computer-mediated communication, social tagging information, search system personalization, new detection mechanisms for the identification of online user groups, and many more. The twelve contributed chapters are extended versions of conference papers as well as completely new invited chapters in the field of social search and recommendation systems. This first-of-its kind survey of current methods will be of interest to researchers from both academia and industry working in the field of social networks.
