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On detecting association-based clique outliers in heterogeneous information networks

Manish Gupta, Jing Gao, Xifeng Yan, Hasan Cam, Jiawei Han
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
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]

Supriya Pandhre, Manish Gupta, Vineeth N Balasubramanian
2017 arXiv   pre-print
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]

Manish Gupta, Arun Mallya, Subhro Roy, Jason H. D. Cho, Jiawei Han
2014 Proceedings of the 2014 SIAM International Conference on Data Mining  
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

Ronald D. Hagan, Michael A. Langston
2021 Algorithms  
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]

Waqas Nawaz
2019 arXiv   pre-print
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]

Manish Gupta, Jing Gao, Jiawei Han
2013 Lecture Notes in Computer Science  
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

Jonathan Kuck, Honglei Zhuang, Xifeng Yan, Hasan Cam, Jiawei Han
2015 International Conference on Extending Database Technology  
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

Pallavi Raj, Rakhi Garg
2020 Indian Journal of Computer Science and Engineering  
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]

Anagi Gamachchi, Serdar Boztas
2018 arXiv   pre-print
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

Debajit Sensarma, Samar Sen Sarma
2015 Indian Journal of Science and Technology  
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]

Lei Tang, Huan Liu
2010 Managing and Mining Graph Data  
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]

Gregory R. Madey, Albert-László Barabási, Nitesh V. Chawla, Marta Gonzalez, David Hachen, Brett Lantz, Alec Pawling, Timothy Schoenharl, Gábor Szabó, Pu Wang, Ping Yan
2007 Lecture Notes in Computer Science  
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]

Amir Gilad, Harsh Parikh, Sudeepa Roy, Babak Salimi
2021 arXiv   pre-print
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

Liviu Badea
2014 Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing  
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

Ravneet Kaur, Sarbjeet Singh
2016 Egyptian Informatics Journal  
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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