Link prediction techniques, applications, and performance: A survey
Link prediction finds missing links (in static networks) or predicts the likelihood of future links
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
(in dynamic networks). The latter definition is useful in network evolution (Wang et al., 2011; …
[HTML][HTML] A survey on literature based discovery approaches in biomedical domain
Abstract Literature Based Discovery (LBD) refers to the problem of inferring new and
interesting knowledge by logically connecting independent fragments of information units …
interesting knowledge by logically connecting independent fragments of information units …
Insider threat detection using a graph-based approach
The authors present the use of graph-based approaches to discovering anomalous
instances of structural patterns in data that represent insider threat activity. The approaches …
instances of structural patterns in data that represent insider threat activity. The approaches …
Netspot: Spotting significant anomalous regions on dynamic networks
How to spot and summarize anomalies in dynamic networks such as road networks,
communication networks and social networks? An anomalous event, such as a traffic …
communication networks and social networks? An anomalous event, such as a traffic …
Discovering structural anomalies in graph-based data
The ability to mine data represented as a graph has become important in several domains
for detecting various structural patterns. One important area of data mining is anomaly …
for detecting various structural patterns. One important area of data mining is anomaly …
Community-based anomaly detection in evolutionary networks
Z Chen, W Hendrix, NF Samatova - Journal of Intelligent Information …, 2012 - Springer
Networks of dynamic systems, including social networks, the World Wide Web, climate
networks, and biological networks, can be highly clustered. Detecting clusters, or …
networks, and biological networks, can be highly clustered. Detecting clusters, or …
Anomaly detection in data represented as graphs
An important area of data mining is anomaly detection, particularly for fraud. However, little
work has been done in terms of detecting anomalies in data that is represented as a graph …
work has been done in terms of detecting anomalies in data that is represented as a graph …
Ranking complex relationships on the semantic web
B Aleman-Meza, C Halaschek-Weiner… - IEEE Internet …, 2005 - ieeexplore.ieee.org
Industry and academia are both focusing their attention on information retrieval over
semantic metadata extracted from the Web, and it is increasingly possible to analyze such …
semantic metadata extracted from the Web, and it is increasingly possible to analyze such …
The case for anomalous link discovery
MJ Rattigan, D Jensen - Acm Sigkdd Explorations Newsletter, 2005 - dl.acm.org
In this paper, we describe the challenges inherent to the task of link prediction, and we
analyze one reason why many link prediction models perform poorly. Specifically, we …
analyze one reason why many link prediction models perform poorly. Specifically, we …
Link discovery in graphs derived from biological databases
P Sevon, L Eronen, P Hintsanen, K Kulovesi… - Data Integration in the …, 2006 - Springer
Public biological databases contain vast amounts of rich data that can also be used to create
and evaluate new biological hypothesis. We propose a method for link discovery in …
and evaluate new biological hypothesis. We propose a method for link discovery in …