People recommendation on social media

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

18 Scopus citations

Abstract

The social web has brought about many new types of recommender systems. One of the most important is recommendation of people, which bears many unique characteristics and challenges. In this chapter, we will review much of the research that has studied people recommendation in social media. The three main types of people recommendation are based on the presumed level of relationship of the user with the recommended individuals and thereby the goal of the recommendation: from recommending familiar people the user may invite to their network or meet at a place, through recommending interesting people the user may subscribe to or follow, to recommending similar people the user may want to get familiarize with. We will demonstrate each of these recommendation types and the techniques used to address them through different case studies. We will also discuss related research areas, summarize key aspects, and suggest future directions.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages570-623
Number of pages54
DOIs
StatePublished - 1 Jan 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10100 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Followee recommendation
  • Friend recommendation
  • People recommendation
  • People recommender systems
  • Profile matching
  • Recommending people
  • Social matching
  • Stranger recommendation

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