Graph and Tensor Mining for fun and profit

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Presentation transcript:

Graph and Tensor Mining for fun and profit Faloutsos Graph and Tensor Mining for fun and profit Luna Dong, Christos Faloutsos Andrey Kan, Jun Ma, Subho Mukherjee Amazon - CMU

Roadmap Introduction – Motivation Part#1: Graphs [break] Faloutsos Roadmap Introduction – Motivation Part#1: Graphs [break] Part#2: Tensors Conclusions KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation KDD 2018 Dong+

Faloutsos Why study graphs? fb>$10B; ~1B users KDD 2018 Dong+

Why study graphs? Internet Map [lumeta.com] Food Web [Martinez ’91] (C) C. Faloutsos, 2017 Why study graphs? Internet Map [lumeta.com] Food Web [Martinez ’91] Friendship Network [Moody ’01] Protein Interactions [genomebiology.com] KDD 2018 Dong+

… e-commerce examples Recommendation systems .... KDD 2018 Dong+ C. Faloutsos e-commerce examples Recommendation systems .... … KDD 2018 Dong+

e-commerce examples Who-buys-what … KDD 2018 Dong+

e-commerce examples Who-buys-what Who-sells-what … KDD 2018 Dong+

e-commerce examples Who-buys-what Who-sells-what Who-reviews-what … … KDD 2018 Dong+

More examples Who-buys-what Who-sells-what Who-reviews-what Who-queries-what Which_machine - connects_to - what … <subject> related-to <object> : graph … … KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation ? ? KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation ? KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation ? KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation ? KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs [break] Faloutsos Roadmap Introduction – Motivation Part#1: Graphs [break] Part#2: Tensors Conclusions KDD 2018 Dong+

Tensors, e.g., time-evolving graphs C. Faloutsos Tensors, e.g., time-evolving graphs What is ‘normal’? suspicious? Groups? … 3am, 4/1 3am, 4/1 10pm, 4/3 11pm, 4/3 KDD 2018 Dong+

Tensors, e.g., MultiView Graph C. Faloutsos Tensors, e.g., MultiView Graph What is ‘normal’? suspicious? Groups? … likes buys reviews buys KDD 2018 Dong+

Tensors, e.g., Knowledge Graph C. Faloutsos Tensors, e.g., Knowledge Graph What is ‘normal’? Forecast? Spot errors? directed … dates … Acted_in born_in … produced KDD 2018 Dong+

‘Recipe’ Structure: Problem definition Short answer/solution LONG answer – details Conclusion/short-answer KDD 2018 Dong+

‘Recipe’ Structure: Problem definition Short answer/solution LONG answer – details Conclusion/short-answer KDD 2018 Dong+

Roadmap Introduction – Motivation Part#1: Graphs Faloutsos Roadmap Introduction – Motivation Part#1: Graphs P1.1: properties/patterns in graphs P1.2: node importance P1.3: community detection P1.4: fraud/anomaly detection P1.5: belief propagation ? ? KDD 2018 Dong+