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On detecting association-based clique outliers in heterogeneous information networks
2013
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13
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We define such anomalous cliques as Association-Based Clique Outliers (ABCOutliers) for heterogeneous information networks, and design effective approaches to detect them. ...
of the associations among entities in the cliques. ...
Given a conjunctive select query, our goal is to detect such unusual clique outliers as Association-Based Clique Outliers (ABCOutliers) in heterogeneous information networks. ...
doi:10.1145/2492517.2492526
dblp:conf/asunam/GuptaGYCH13
fatcat:m7ayugsp7veqra2xeh4ydxpudm
Community-based Outlier Detection for Edge-attributed Graphs
[article]
2017
arXiv
pre-print
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Beyond graph analysis tasks like graph query processing, link analysis, influence propagation, there has recently been some work in the area of outlier detection for information network data. ...
Experimental results on synthetic datasets and the DBLP dataset show the effectiveness of our approach for finding novel outliers from networks. ...
Community-based outlier detection has been studied both for static networks and dynamic networks. ...
arXiv:1612.09435v2
fatcat:rdp4inepnjhofh65eoqrx5pcva
Local Learning for Mining Outlier Subgraphs from Network Datasets
[chapter]
2014
Proceedings of the 2014 SIAM International Conference on Data Mining
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Similarly, having one of the authors in the clique as a theory author when all other authors (both in the clique and neighborhood) are data mining authors, is also suspicious. ...
The probability of an edge can in turn be modeled based on the weighted similarity between the attribute values of the nodes linked by the edge. ...
Acknowledgements The work was supported in part by the U. We would also like to thank the Institute for Genomic Biology at University of Illinois, Urbana Champaign for their equipment. ...
doi:10.1137/1.9781611973440.9
dblp:conf/sdm/GuptaMRCH14
fatcat:lrptpcgoabg4fczrohtvmapjyi
Molecular Subtyping and Outlier Detection in Human Disease Using the Paraclique Algorithm
2021
Algorithms
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A graph theoretical approach based on the paraclique algorithm is described that can easily be employed to identify putative disease subtypes and serve as an aid in outlier detection as well. ...
At the same time, techniques based on graph clustering, particularly clique-based strategies, have been successfully used to identify disease biomarkers and gene networks. ...
Although clique-based methods have been used as a basis for tasks such as biomarker detection and gene network elucidation, disease subtyping has received surprisingly little attention. ...
doi:10.3390/a14020063
fatcat:ahy5neep3vbu7psul4nu26hfv4
An Empirical Study of Community Detection Algorithms on Social and Road Networks
[article]
2019
arXiv
pre-print
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Community detection in social networks is a problem with considerable interest, since, discovering communities reveals hidden information about networks. ...
There exist many algorithms to detect inherent community structures and recently few of them are investigated on social networks. ...
This algorithm requires to select initial k leaders as the number of desired communities. • Sequential Clique Percolation (SCP) [5] algorithm is based on the clique percolation method and detects k-clique ...
arXiv:1911.08992v1
fatcat:ksx4gvtednanjaahrfkryrk4te
Community Distribution Outlier Detection in Heterogeneous Information Networks
[chapter]
2013
Lecture Notes in Computer Science
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detect outliers based on such patterns. ...
Rich information associated with multi-typed nodes in heterogeneous networks motivates us to propose a new definition of outliers, which is different from those defined for homogeneous networks. ...
Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. ...
doi:10.1007/978-3-642-40988-2_36
fatcat:jzf3ku2emfggjo27ouahyqzxha
Query-Based Outlier Detection in Heterogeneous Information Networks
2015
International Conference on Extending Database Technology
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In this study, we introduce the concept of query-based outlier in heterogeneous information networks, design a query language to facilitate users to specify such queries flexibly, define a good outlier ...
Our experiments on real data sets show that following such a methodology, interesting outliers can be defined and uncovered flexibly and effectively in large heterogeneous networks. ...
[9] also studied outlier detection based on assumption of association-based cliques in networks. ...
doi:10.5441/002/edbt.2015.29
pmid:27064397
pmcid:PMC4825692
dblp:conf/edbt/KuckZYCH15
fatcat:r6xilqa7ardjtbdkroxtqtsg3e
SOME OBSERVATION OF ALGORITHMS DEVELOPED FOR ANOMALY DETECTION
2020
Indian Journal of Computer Science and Engineering
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This paper mainly focuses on the graph mining techniques used for anomaly detection in social networks. ...
Using anomaly detection techniques, we can identify the unusual behavior of such users. In social networks, anomalies can be detected by exploring the pattern hidden in the network. ...
. • SODA-Various work has been done in the area of detecting subgraph outliers, but they only focus on detecting outliers for the whole network or in a community. ...
doi:10.21817/indjcse/2020/v11i1/201101005
fatcat:ynz45figozbu7fuznqo2u3j55y
Insider Threat Detection Through Attributed Graph Clustering
[article]
2018
arXiv
pre-print
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Thus it creates a high dimensional, heterogeneous data analysis problem in isolating suspicious users. ...
This research work proposes an insider threat detection framework, which utilizes the attributed graph clustering techniques and outlier ranking mechanism for enterprise users. ...
In addition, Anagi Gamachchi is supported by an "Australian Government Research Training Program Scholarship". ...
arXiv:1809.00231v1
fatcat:nivhzowh4fbq5c7gk5pqh3has4
A Survey on Different Graph Based Anomaly Detection Techniques
2015
Indian Journal of Science and Technology
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This survey paper cites some methods of graph based anomaly detection in the field of information security, finance, cybersecurity, online social networks, health care, law enforcement etc. and their classification ...
to improve the technique of detecting anomalies in data has been given. ...
Review graph based online store review spammer detection 18
Anomalies in opinion networks Heterogeneous review graph concept is used to capture the relationship among reviewers, review and stores ...
doi:10.17485/ijst/2015/v8i1/75197
fatcat:2eckrpzh6va7dmixqooukngtly
Graph Mining Applications to Social Network Analysis
[chapter]
2010
Managing and Mining Graph Data
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Network classification and outlier detection. Some actors are labeled with certain information. ...
As most networks demonstrate strong community structures, one basic task in social network analysis is community detection which uncovers the group membership of actors in a network. ...
Hierarchy-Centric Community Detection Another line of community detection is to build a hierarchical structure of communities based on network topology. ...
doi:10.1007/978-1-4419-6045-0_16
dblp:series/ads/TangL10
fatcat:ydikf7xblvah5a36nazj6idwje
Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management
[chapter]
2007
Lecture Notes in Computer Science
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Powered-on cell phones maintain contact with one or more within-range cell towers so as to receive incoming calls. ...
The system is designed to use real-time cell phone calling data from a geographical region, including calling activity -who calls whom, call duration, services in use, and cell phone location information ...
We believe that our approach has promise for clustering and outlier detection on streaming data in the WIPER Detection and Alert System [10] . ...
doi:10.1007/978-3-540-72584-8_143
fatcat:hopkqjbguvgyzpw7untlh5x7ru
Heterogeneous Treatment Effects in Social Networks
[article]
2021
arXiv
pre-print
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We perform extensive experimental evaluations with a real development economics dataset about the treatment effect of belonging to a financial support network called self-help groups on risk tolerance, ...
In addition, we develop a novel algorithm for the discovery of network patterns that are potential effect modifiers. ...
In addition, there has been work on detecting the equivalence of actors based on their ego-centric graph [16, 43] . ...
arXiv:2105.10591v5
fatcat:necdgfjep5akrdsmpgwmmnb2ba
Extracting significant sample-specific cancer mutations using their protein interactions
2014
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
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The use of pp interactions is based on our surprising finding that most AML mutations tend to affect nontrivial protein to protein interaction cliques. ...
Given the low incidence of most mutations in virtually all cancer types, as well as the significant inter-patient heterogeneity of the mutation landscape, determining the true causal mutations in each ...
For example, the NPM1 gene is placed by the TCGA study in a category of its own, solely based on its high mutation rate in AML. ...
pmid:24297530
fatcat:y7oogqy6zrcchijl5zfeiuxvom
A survey of data mining and social network analysis based anomaly detection techniques
2016
Egyptian Informatics Journal
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A special reference is made to the analysis of social network centric anomaly detection techniques which are broadly classified as behavior based, structure based and spectral based. ...
This paper discusses different types of anomalies and their novel categorization based on various characteristics. ...
Based on information available in network/graph structure [13] Depending upon the type of information available at a node or an edge, anomalies can be categorized as labeled or unlabeled. ...
doi:10.1016/j.eij.2015.11.004
fatcat:jixqyc6p5vfx5kkiczcwtt32fy
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