FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4283827423> ?p ?o ?g. }

• W4283827423 endingPage "37" @default.
• W4283827423 startingPage "1" @default.
• W4283827423 abstract "Much of today’s data are represented as graphs, ranging from social networks to bibliographic citations. Nodes in such graphs correspond to records that generally represent entities, while edges represent relationships between these entities. Both nodes and edges in a graph can have attributes that characterize the entities and their relationships. Relationships are either explicitly known (like friends in a social network), or they are inferred using link prediction (such as two babies are siblings because they have the same mother). Any graph representing real-world data likely contains nodes and edges that are abnormal, and identifying these can be important for outlier detection in applications ranging from crime and fraud detection to viral marketing. We propose a novel approach to the unsupervised detection of abnormal nodes and edges in graphs. We first characterize nodes and edges using a set of features, and then employ a one-class classifier to identify abnormal nodes and edges. We extract patterns of features from these abnormal nodes and edges, and apply clustering to identify groups of patterns with similar characteristics. We finally visualize these abnormal patterns to show co-occurrences of features and relationships between those features that mostly influence the abnormality of nodes and edges. We evaluate our approach on datasets from diverse domains, including historical birth certificates, COVID patient records, e-mails, books, and movies. This evaluation demonstrates that our approach is well suited to identify both abnormal nodes and edges in graphs in an unsupervised way, and it can outperform several baseline anomaly detection techniques." @default.
• W4283827423 created "2022-07-07" @default.
• W4283827423 creator A5002321076 @default.
• W4283827423 creator A5022945960 @default.
• W4283827423 creator A5029234658 @default.
• W4283827423 creator A5060825460 @default.
• W4283827423 date "2022-12-28" @default.
• W4283827423 modified "2023-10-17" @default.
• W4283827423 title "Unsupervised Identification of Abnormal Nodes and Edges in Graphs" @default.
• W4283827423 cites W1843749293 @default.
• W4283827423 cites W1976526581 @default.
• W4283827423 cites W1981496511 @default.
• W4283827423 cites W1996851530 @default.
• W4283827423 cites W2033083678 @default.
• W4283827423 cites W2034572462 @default.
• W4283827423 cites W2056081083 @default.
• W4283827423 cites W2057212005 @default.
• W4283827423 cites W2061122559 @default.
• W4283827423 cites W2062769337 @default.
• W4283827423 cites W2087615914 @default.
• W4283827423 cites W2089554624 @default.
• W4283827423 cites W2122646361 @default.
• W4283827423 cites W2132870739 @default.
• W4283827423 cites W2134008243 @default.
• W4283827423 cites W2137130182 @default.
• W4283827423 cites W2147505890 @default.
• W4283827423 cites W2147620601 @default.
• W4283827423 cites W2161920802 @default.
• W4283827423 cites W2162774438 @default.
• W4283827423 cites W2170902455 @default.
• W4283827423 cites W2293888039 @default.
• W4283827423 cites W2337116603 @default.
• W4283827423 cites W2342204193 @default.
• W4283827423 cites W2741114205 @default.
• W4283827423 cites W2788534864 @default.
• W4283827423 cites W2808544127 @default.
• W4283827423 cites W2906836970 @default.
• W4283827423 cites W2940272626 @default.
• W4283827423 cites W2944250323 @default.
• W4283827423 cites W2953468444 @default.
• W4283827423 cites W2963395938 @default.
• W4283827423 cites W2963486145 @default.
• W4283827423 cites W2972079061 @default.
• W4283827423 cites W2978834584 @default.
• W4283827423 cites W2997591727 @default.
• W4283827423 cites W2998647325 @default.
• W4283827423 cites W3010795489 @default.
• W4283827423 cites W3037008030 @default.
• W4283827423 cites W3047751072 @default.
• W4283827423 cites W3096561660 @default.
• W4283827423 cites W3099616155 @default.
• W4283827423 cites W3101470767 @default.
• W4283827423 cites W3119464161 @default.
• W4283827423 cites W3203712260 @default.
• W4283827423 cites W4210754024 @default.
• W4283827423 cites W4239954780 @default.
• W4283827423 cites W4254182148 @default.
• W4283827423 doi "https://doi.org/10.1145/3546912" @default.
• W4283827423 hasPublicationYear "2022" @default.
• W4283827423 type Work @default.
• W4283827423 citedByCount "1" @default.
• W4283827423 countsByYear W42838274232023 @default.
• W4283827423 crossrefType "journal-article" @default.
• W4283827423 hasAuthorship W4283827423A5002321076 @default.
• W4283827423 hasAuthorship W4283827423A5022945960 @default.
• W4283827423 hasAuthorship W4283827423A5029234658 @default.
• W4283827423 hasAuthorship W4283827423A5060825460 @default.
• W4283827423 hasBestOaLocation W42838274231 @default.
• W4283827423 hasConcept C116834253 @default.
• W4283827423 hasConcept C124101348 @default.
• W4283827423 hasConcept C132525143 @default.
• W4283827423 hasConcept C153180895 @default.
• W4283827423 hasConcept C154945302 @default.
• W4283827423 hasConcept C15744967 @default.
• W4283827423 hasConcept C177264268 @default.
• W4283827423 hasConcept C199360897 @default.
• W4283827423 hasConcept C41008148 @default.
• W4283827423 hasConcept C50965678 @default.
• W4283827423 hasConcept C59822182 @default.
• W4283827423 hasConcept C73555534 @default.
• W4283827423 hasConcept C739882 @default.
• W4283827423 hasConcept C77805123 @default.
• W4283827423 hasConcept C79337645 @default.
• W4283827423 hasConcept C80444323 @default.
• W4283827423 hasConcept C86803240 @default.
• W4283827423 hasConcept C95623464 @default.
• W4283827423 hasConceptScore W4283827423C116834253 @default.
• W4283827423 hasConceptScore W4283827423C124101348 @default.
• W4283827423 hasConceptScore W4283827423C132525143 @default.
• W4283827423 hasConceptScore W4283827423C153180895 @default.
• W4283827423 hasConceptScore W4283827423C154945302 @default.
• W4283827423 hasConceptScore W4283827423C15744967 @default.
• W4283827423 hasConceptScore W4283827423C177264268 @default.
• W4283827423 hasConceptScore W4283827423C199360897 @default.
• W4283827423 hasConceptScore W4283827423C41008148 @default.
• W4283827423 hasConceptScore W4283827423C50965678 @default.
• W4283827423 hasConceptScore W4283827423C59822182 @default.
• W4283827423 hasConceptScore W4283827423C73555534 @default.

• next