Social search

Peter Brusilovsky, Barry Smyth, Bracha Shapira

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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 languageAmerican English
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages213-276
Number of pages64
ISBN (Electronic)978-3-319-90092-6
ISBN (Print)978-3-319-90091-9
DOIs
StatePublished - 3 May 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10100 LNCS

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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