Social Search

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Title: Social Search
Authors: Brusilousky, Peter
Smyth, Barry
Shapira, Bracha
Permanent link: http://hdl.handle.net/10197/10400
Date: 3-May-2018
Online since: 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.
Funding Details: Science Foundation Ireland
Type of material: Book Chapter
Publisher: Springer
Series/Report no.: Lecture Notes in Computer Science book series (LNCS); Volume 10100
Copyright (published version): 2018 Springer International Publishing AG
Keywords: Recommender systemsWeb search enginesInformation retrievalSocial search landscape
DOI: 10.1007/978-3-319-90092-6_7
Language: en
Status of Item: Peer reviewed
ISBN: 978-3-319-90092-6
Appears in Collections:Insight Research Collection

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