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Local Pattern Detection in Attributed Graphs [chapter]

Jean-François Boulicaut, Marc Plantevit, Céline Robardet
2016 Lecture Notes in Computer Science  
Mining topological patterns relies on frequent pattern mining and graph topology analysis to reveal the links that exist between the relation encoded by the graph and the vertex attributes.  ...  We propose to mine the topology of a large attributed graph by finding regularities among vertex descriptors.  ...  Doing so, we emphasize powerful mechanisms for detecting new types of local patterns in interaction graphs.  ... 
doi:10.1007/978-3-319-41706-6_8 fatcat:hotg2gtv3jawhf7hdbsu4o4zi4

Mining communities and their descriptions on attributed graphs: a survey

Martin Atzmueller, Stephan Günnemann, Albrecht Zimmermann
2021 Data mining and knowledge discovery  
There exists already a remarkable body of work that attempts to find communities in vertex-attributed graphs that are relatively homogeneous with respect to attribute values.  ...  AbstractFinding communities that are not only relatively densely connected in a graph but that also show similar characteristics based on attribute information has drawn strong attention in the last years  ...  Therefore, in an unsupervised view on local pattern detection, no information but the data itself is given to find out what patterns may be present in the database.  ... 
doi:10.1007/s10618-021-00741-z fatcat:gw6xnww5gzb27aky5bdpmmp7fe

Subgroup and Community Analytics on Attributed Graphs

Martin Atzmueller
2015 International Conference on Formal Concept Analysis  
We present an organized picture of recent research in subgroup discovery and community detection specifically focusing on attributed graphs.  ...  That is, we include complex relational graphs that are annotated with additional information, e.g., attribute information on the nodes and/or edges of the graph.  ...  to a local model derived from a set of attributes.  ... 
dblp:conf/icfca/Atzmueller15 fatcat:uhrguoxntzbcvgjolkneyhyayq

MinerLSD: efficient mining of local patterns on attributed networks

Martin Atzmueller, Henry Soldano, Guillaume Santini, Dominique Bouthinon
2019 Applied Network Science  
In this paper, we present MinerLSD, a method for efficient local pattern mining on attributed networks.  ...  In addition, we exploit efficient techniques for pruning the pattern space: We adapt a local variant of the standard Modularity metric used in community detection that is extended using optimistic estimates  ...  Acknowledgements Martin Atzmueller was supported in part by Université Sorbonne Paris Cité as a visiting professor.  ... 
doi:10.1007/s41109-019-0155-y fatcat:giqby2dhljd55oxndrij6dxddm

Pattern-based design recovery of Java software

Jochen Seemann, Jürgen Wolff von Gudenberg
1998 Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering - SIGSOFT '98/FSE-6  
We take a pattern-based approach and proceed in a step by step manner deriving several layers of increasing abstraction.  ...  We define criteria for the automatic detection of associations and aggregations between classes, as well as for some of the popular design patterns such as composite or strategy.  ...  In order to prepare the transformations we always start matching patterns in the most abstract graph, and hence decrease our search space for the detection of more detailed patterns.  ... 
doi:10.1145/288195.288207 dblp:conf/sigsoft/SeemannG98 fatcat:2t32qidlpjfcxcnzklr5njlpce

Reconstruction Enhanced Multi-View Contrastive Learning for Anomaly Detection on Attributed Networks [article]

Jiaqiang Zhang, Senzhang Wang, Songcan Chen
2022 arXiv   pre-print
Detecting abnormal nodes from attributed networks is of great importance in many real applications, such as financial fraud detection and cyber security.  ...  This task is challenging due to both the complex interactions between the anomalous nodes with other counterparts and their inconsistency in terms of attributes.  ...  tions [Liu et al., 2021a].We adopt the node-subgraph matching pattern based pretext task which is proved useful for the anomaly detection on attributed networks[Liu et al., 2021b].Meanwhile, the graph  ... 
arXiv:2205.04816v1 fatcat:r6v76enibnaqzne3hrgbv6i3oi

Detecting Localized Categorical Attributes on Graphs

Siheng Chen, Yaoqing Yang, Shi Zong, Aarti Singh, Jelena Kovacevic
2017 IEEE Transactions on Signal Processing  
We propose two statistics: graph wavelet statistic and graph scan statistic, both of which are provably effective in detecting localized attributes.  ...  In other words, nodes activated by an attribute form a subgraph that can be easily separated from other nodes. In this paper, we thus focus on the task of detecting localized attributes on a graph.  ...  We use the graph wavelet basis to detect the structurecorrelated patterns.  ... 
doi:10.1109/tsp.2017.2666772 fatcat:eg52lfvcy5gk7dpf6govfwcknq

Finding the Most Descriptive Substructures in Graphs with Discrete and Numeric Labels [chapter]

Michael Davis, Weiru Liu, Paul Miller
2013 Lecture Notes in Computer Science  
We explore the relationship between graph structure and the distribution of attribute values and propose an outlier-detection step, which is used as a constraint during substructure discovery.  ...  Many graph datasets are labelled with discrete and numeric attributes.  ...  thank Erich Schubert at Ludwig-Maximilians Universität München for assistance with verifying our LOF implementation and providing us with the RP + PINN + LOF implementation ahead of its official release in  ... 
doi:10.1007/978-3-642-37382-4_10 fatcat:hvz3v7p3orbwnofe5dv5je7mre

Finding the most descriptive substructures in graphs with discrete and numeric labels

Michael Davis, Weiru Liu, Paul Miller
2013 Journal of Intelligent Information Systems  
We explore the relationship between graph structure and the distribution of attribute values and propose an outlier-detection step, which is used as a constraint during substructure discovery.  ...  Many graph datasets are labelled with discrete and numeric attributes.  ...  thank Erich Schubert at Ludwig-Maximilians Universität München for assistance with verifying our LOF implementation and providing us with the RP + PINN + LOF implementation ahead of its official release in  ... 
doi:10.1007/s10844-013-0299-7 fatcat:eqrepgrfi5bi3pwcoiol6ygura

Description-oriented community detection using exhaustive subgroup discovery

Martin Atzmueller, Stephan Doerfel, Folke Mitzlaff
2016 Information Sciences  
Essentially, we mine patterns in the "description space" characterizing interesting sets of nodes (i. e., subgroups) in the "graph space"; the interestingness of a community is evaluated by a selectable  ...  Communities can intuitively be defined as subsets of nodes of a graph with a dense structure in the corresponding subgraph.  ...  Additionally, not only the (plain) graph structure is exploited for detecting communities, but also descriptive information contained in the attributed graph is used in a description-oriented way, while  ... 
doi:10.1016/j.ins.2015.05.008 fatcat:xvaj7mqedbbt7n3wcc5yineffu

Quick survey of graph-based fraud detection methods [article]

Paul Irofti, Andrei Patrascu, Andra Baltoiu
2021 arXiv   pre-print
We present a survey on anomaly detection techniques used for fraud detection that exploit both the graph structure underlying the data and the contextual information contained in the attributes.  ...  In general, anomaly detection is the problem of distinguishing between normal data samples with well defined patterns or signatures and those that do not conform to the expected profiles.  ...  In Section 2 (Locality) we survey methods that examine the local patterns of the graph, by working with neighborhoods.  ... 
arXiv:1910.11299v3 fatcat:zyupd4ezxrgw3f7g5utzihy6qi

Socrates

C. Savkli, R. Carr, M. Chapman, B. Chee, D. Minch
2014 2014 IEEE High Performance Extreme Computing Conference (HPEC)  
A distributed semantic graph processing system that provides locality control, indexing, graph query, and parallel processing capabilities is presented.  ...  Indexing Graph Attributes Socrates stores vertex and edge attributes following the following principles: • Every attribute type is stored in its own two column table (primary key & value) • All attributes  ...  by JDBC  Each machine runs a server that processes the query in parallel Processing: • Submitting jobs that are executed in parallel on local graphs • Communication provided by JMS • Jobs are  ... 
doi:10.1109/hpec.2014.7040993 dblp:conf/hpec/SavkliCCCM14 fatcat:mfjb44h2gzbfxcjr3mt343ikvy

Visual Graph Mining [article]

Quanshi Zhang, Xuan Song, Ryosuke Shibasaki
2017 arXiv   pre-print
In general, visual knowledge can usually be modeled as attributed relational graphs (ARGs) with local attributes representing local parts and pairwise attributes describing the spatial relationship between  ...  Common subgraphs hidden in these ARGs usually have soft attributes, with considerable inter-graph variation.  ...  local and pairwise attributes.  ... 
arXiv:1708.03921v1 fatcat:jzhldngcl5gu5fgu5fjgvj42j4

Anomaly Detection on Attributed Networks via Contrastive Self-Supervised Learning [article]

Yixin Liu, Zhao Li, Shirui Pan, Chen Gong, Chuan Zhou, George Karypis
2021 arXiv   pre-print
Anomaly detection on attributed networks attracts considerable research interests due to wide applications of attributed networks in modeling a wide range of complex systems.  ...  Meanwhile, a well-designed graph neural network-based contrastive learning model is proposed to learn informative embedding from high-dimensional attributes and local structure and measure the agreement  ...  For the normal instance in graphs, there is a potential matching pattern between each node and its neighbors, e.g., the homophily hypothesis.  ... 
arXiv:2103.00113v1 fatcat:gep7h2b4qrhzxbpnqsjbu7xmsi

Mining And-Or Graphs for Graph Matching and Object Discovery

Quanshi Zhang, Ying Nian Wu, Song-Chun Zhu
2015 2015 IEEE International Conference on Computer Vision (ICCV)  
Given a set of attributed relational graphs (ARGs), we propose to use a hierarchical And-Or Graph (AoG) to model the pattern of maximal-size common subgraphs embedded in the ARGs, and we develop a general  ...  This paper reformulates the theory of graph mining on the technical basis of graph matching, and extends its scope of applications to computer vision.  ...  Each OR node describes a local part and has several alternative terminal nodes as local pattern candidates.  ... 
doi:10.1109/iccv.2015.15 dblp:conf/iccv/ZhangWZ15 fatcat:57net2pgz5ahxoqipuf6j7i6au
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