TY - CHAP
T1 - A survey on proximity measures for social networks
AU - Cohen, Sara
AU - Kimelfeld, Benny
AU - Koutrika, Georgia
PY - 2012
Y1 - 2012
N2 - Measuring proximity in a social network is an important task, with many interesting applications, including person search and link prediction. Person search is the problem of finding, by means of keyword search, relevant people in a social network. In user-centric person search, the search query is issued by a person participating in the social network and the goal is to find people that are relevant not only to the keywords, but also to the searcher herself. Link prediction is the task of predicting new friendships (links) that are likely to be added to the network. Both of these tasks require the ability to measure proximity of nodes within a network, and are becoming increasingly important as social networks become more ubiquitous. This chapter surveys recent work on scoring measures for determining proximity between nodes in a social network.We broadly identify various classes of measures and discuss prominent examples within each class. We also survey efficient implementations for computing or estimating the values of the proximity measures.
AB - Measuring proximity in a social network is an important task, with many interesting applications, including person search and link prediction. Person search is the problem of finding, by means of keyword search, relevant people in a social network. In user-centric person search, the search query is issued by a person participating in the social network and the goal is to find people that are relevant not only to the keywords, but also to the searcher herself. Link prediction is the task of predicting new friendships (links) that are likely to be added to the network. Both of these tasks require the ability to measure proximity of nodes within a network, and are becoming increasingly important as social networks become more ubiquitous. This chapter surveys recent work on scoring measures for determining proximity between nodes in a social network.We broadly identify various classes of measures and discuss prominent examples within each class. We also survey efficient implementations for computing or estimating the values of the proximity measures.
UR - http://www.scopus.com/inward/record.url?scp=84892930014&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34213-4_13
DO - 10.1007/978-3-642-34213-4_13
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AN - SCOPUS:84892930014
SN - 9783642342127
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 191
EP - 206
BT - Search Computing
A2 - Ceri, Stefano
A2 - Brambilla, Marco
ER -