Link mining: a survey

By Lise Getoor, Christopher P. Diehl. SKDD, 2005

1,113 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/4c3bce670150c86905e3c21e0b745a346fb4d068

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Citations in the corpus

You are what you like! Information leakage through users' Interests (2012, methodology): “Our technique consists of four main steps as illustrated by Figure 1: 1.”
Predicting missing links via local information (2009, positive): “diction have used some external information besides the network topology [ 10 ].”
Toward link predictability of complex networks (2015, background): “The link prediction problem has been a long-standing challenge in modern information science (13, 49).”
Knowledge graph refinement: A survey of approaches and evaluation methods (2016, background): “, they are a variant of link-based classification problems [31].”
K-isomorphism: privacy preserving network publication against structural attacks (2010, background): “[10] is a survey on link mining for datasets that resemble social networks, while [21] considers topic and role discovery in social networks.”
Co-author Relationship Prediction in Heterogeneous Bibliographic Networks (2011, background): “A good survey on link prediction may be found in [3].”
RDF-3X: a RISC-style engine for RDF (2008, methodology): “prevalent methods in that line of research [16, 44, 49], e.”
Inferring anchor links across multiple heterogeneous social networks (2013, neutral): “Copyright 2013 ACM 978-1-4503-2263-8/13/10 ...$15.00. http://dx.doi.org/10.1145/2505515.2505531.”
The RDF-3X engine for scalable management of RDF data (2010, methodology): “While it may seem that this is a standard graph-mining issue, the prevalent methods in that line of research [19,59,67], e.”
Clustering attributed graphs: Models, measures and methods (2015, methodology): “Several graph mining tasks have been extended to attributed graphs, like link prediction (Getoor & Diehl, 2005; Rossetti et al., 2011; Gong et al., 2011; Sun et al., 2012) or attribute inference (Li & Yeung, 2009; Gong et al., 2011; Yang et al., 2011).”
Preserving the Privacy of Sensitive Relationships in Graph Data (2007, background): “They have been studied in the link mining community [6], and the techniques developed for collective classification, object identification and link prediction can be used to learn hidden properties of the data.”
A Review of Relational Machine Learning for Knowledge Graphs (2015, background): “It has been shown that relational models which take the relationships of entities into account can signiﬁcantly outperform non-relational ML methods for this task (e.g., see [40, 41]).”
Link prediction in social networks: the state-of-the-art (2014, background): “Being one of the link mining and analyzing tasks [105], link prediction has many important applications.”
Towards identity anonymization on graphs (2008, background): “The structure queries check the existence of neighbors of a node or the structure of the subgraph in the vicinity of a node.”