Matches in SemOpenAlex for { <https://semopenalex.org/work/W2949202899> ?p ?o ?g. }
- W2949202899 abstract "Link recommendation has attracted significant attentions from both industry practitioners and academic researchers. In industry, link recommendation has become a standard and most important feature in online social networks, prominent examples of which include People You May Know on LinkedIn and You May Know on Google+. In academia, link recommendation has been and remains a highly active research area. This paper surveys state-of-the-art link recommendation methods, which can be broadly categorized into learning-based methods and proximity-based methods. We further identify social and economic theories, such as social interaction theory, that underlie these methods and explain from a theoretical perspective why a link recommendation method works. Finally, we propose to extend link recommendation research in several directions that include utility-based link recommendation, diversity of link recommendation, link recommendation from incomplete data, and experimental study of link recommendation." @default.
- W2949202899 created "2019-06-27" @default.
- W2949202899 creator A5015643883 @default.
- W2949202899 creator A5077260842 @default.
- W2949202899 creator A5078410186 @default.
- W2949202899 date "2015-11-05" @default.
- W2949202899 modified "2023-09-27" @default.
- W2949202899 title "A Survey of Link Recommendation for Social Networks: Methods, Theoretical Foundations, and Future Research Directions" @default.
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