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Social Search

Author(s)
Brusilousky, Peter  
Smyth, Barry  
Shapira, Bracha  
Uri
http://hdl.handle.net/10197/10400
Date Issued
2018-05-03
Date Available
2019-05-13T08:57:37Z
Abstract
Today, most people find what they are looking for online by using search engines such as Google, Bing, or Baidu. Modern web search engines have evolved from their roots in information retrieval to developing new ways to cope with the unique nature of web search. In this chapter, we review recent research that aims to make search a more social activity by combining readily available social signals with various strategies for using these signals to influence or adapt more conventional search results. The chapter begins by framing the social search landscape in terms of the sources of data available and the ways in which this can be leveraged before, during, and after search. This includes a number of detailed case studies that serve to mark important milestones in the evolution of social search research and practice.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Book Chapter
Publisher
Springer
Series
Lecture Notes in Computer Science book series (LNCS)
Volume 10100
Copyright (Published Version)
2018 Springer International Publishing AG
Subjects

Recommender systems

Web search engines

Information retrieval...

Social search landsca...

DOI
10.1007/978-3-319-90092-6_7
Language
English
Status of Item
Peer reviewed
ISBN
978-3-319-90092-6
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
No Thumbnail Available
Name

insight_publication.pdf

Size

5.74 MB

Format

Adobe PDF

Checksum (MD5)

83ed71629794467a766b06b3cb679baf

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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