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Social search

Brusilovsky, P and Smyth, B and Shapira, B (2018) Social search. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). UNSPECIFIED, 213 - 276. ISBN UNSPECIFIED

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Abstract

© Springer International Publishing AG, part of Springer Nature 2018. 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.


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Details

Item Type: Book Section
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Smyth, B
Shapira, B
Date: 1 January 2018
Date Type: Publication
Volume: 10100
Page Range: 213 - 276
DOI or Unique Handle: 10.1007/978-3-319-90092-6_7
Schools and Programs: School of Computing and Information > Information Science
Refereed: Yes
Title of Book: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Date Deposited: 27 Jul 2018 18:58
Last Modified: 01 Aug 2019 12:56
URI: http://d-scholarship.pitt.edu/id/eprint/34610

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