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Graph Classification: A Comparison Study 02/04/19 Presented by: Camilo Muoz Juan Carrillo Graph Classification Graph Classification: A Comparison Study PAGE 2 Graph Classification Induce a mapping f(x) : X {1} given a set of

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Graph Classification: A Comparison Study

Presented by: Camilo Muñoz Juan Carrillo

02/04/19

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Graph Classification

Graph Classification: A Comparison Study

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Graph Classification

Graph Classification: A Comparison Study

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Induce a mapping f(x) : X → {±1} given a set of training samples Action Comedy Romance Sci-fi Input graph Label Classifier

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Graph Classification

Graph Classification: A Comparison Study

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Kernel methods Sequential methods Embedding methods

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The Comparison Study

Graph Classification: A Comparison Study

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Kernel CNN (KCNN)
Deep Graph Kernels (DGK)
graph2vec >> Embedding
Multi-hop Assortativity (MHA)

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Motivation

Graph Classification: A Comparison Study

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Lack of evaluation of graph similarity techniques across categories
Lack of experimental evaluation regarding multiclass classification

https://ls11-www.cs.tu-dortmund.de/staff/morris/graph kerneldatasets

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Graph Classification: A Comparison Study

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Kernel CNN (KCNN)

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Graph Classification: A Comparison Study

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Kernel CNN (KCNN)

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Deep Graph Kernels

Graph Classification: A Comparison Study

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Deep Graph Kernels

Graph Classification: A Comparison Study

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Graph Classification: A Comparison Study

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graph2vec

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Graph Classification: A Comparison Study

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graph2vec

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Graph Classification: A Comparison Study

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Multi-hop Assortativity (MHA)

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Graph Classification: A Comparison Study

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Multi-hop Assortativity (MHA)

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Experimental Evaluation

Graph Classification: A Comparison Study

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RQ1: How can the nature of the graph data (e.g. number of nodes,

average number of edges per node) impact the performance of the techniques?

RQ2: Is there a clear difference in performance when using binary

classification datasets versus using multiclass graph data?

RQ3: Is there a technique that clearly outperforms the others in

terms of performance?

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Microsoft datasets

Graph Classification: A Comparison Study

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Semantic image processing
The class for each graph

corresponds to its semantic

meaning. For example building,

grass, tree, face, car, bicycle

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First-MM dataset

Graph Classification: A Comparison Study

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First-MM stands for Flexible Skill

Acquisition and Intuitive Robot Tasking for Mobile Manipulation in the Real World

The graphs represent 3d point

clouds of household objects

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IMDb datasets

Graph Classification: A Comparison Study

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Movie collaboration graphs
The class correspond to the genre of

the movie such as Action, Romance, Comedy, and Sci-Fi

User discussion datasets
Binary dataset contains posts from 4

popular subreddits: IAmA, AskReddit, TrollXChromosomes, and atheism

Multiclass dataset contains posts from

5 subreddits: worldnews, videos, AdviceAnimals, aww, and mildlyinteresting

Reddit datasets

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Experimental Evaluation

Graph Classification: A Comparison Study

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Experimental Setup

Graph Classification: A Comparison Study

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Dataset preprocessing
Code customization
Selection of initialization parameters
Graph transformation technique
Graph Classification

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Evaluation Metrics

Graph Classification: A Comparison Study

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Mean prediction accuracies and standard deviations
Graph transformation runtime
Additional storage required for transformed data

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Evaluation Results

Graph Classification: A Comparison Study

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Mean prediction accuracies and standard deviations

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Evaluation Results

Graph Classification: A Comparison Study

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Evaluation Results

Graph Classification: A Comparison Study

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Graph transformation runtime

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Evaluation Results

Graph Classification: A Comparison Study

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Additional storage required for transformed data

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Potential Extensions

Graph Classification: A Comparison Study

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Discussion

Graph Classification: A Comparison Study

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Appendix

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