Social search

Peter Brusilovsky; Barry Smyth; Bracha Shapira

doi:10.1007/978-3-319-90092-6_7

Social search

Peter Brusilovsky, Barry Smyth, Bracha Shapira

Department of Software and Information Systems Engineering

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

15 Scopus citations

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.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	213-276
Number of pages	64
DOIs	https://doi.org/10.1007/978-3-319-90092-6_7
State	Published - 1 Jan 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10100 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science (all)

Access to Document

10.1007/978-3-319-90092-6_7

Cite this

Brusilovsky, P., Smyth, B., & Shapira, B. (2018). Social search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 213-276). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10100 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-90092-6_7

Brusilovsky, Peter ; Smyth, Barry ; Shapira, Bracha. / Social search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2018. pp. 213-276 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Brusilovsky, P, Smyth, B & Shapira, B 2018, Social search. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10100 LNCS, Springer Verlag, pp. 213-276. https://doi.org/10.1007/978-3-319-90092-6_7

Social search. / Brusilovsky, Peter; Smyth, Barry; Shapira, Bracha.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2018. p. 213-276 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10100 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

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Brusilovsky P, Smyth B, Shapira B. Social search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2018. p. 213-276. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-90092-6_7

Social search

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