CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

Title

CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

Role

Editor: CIKM '15 Conference Committee

Contributing authors: Haishuai Wang, Peng Zhang, Ivor Tsang, Ling Chen, Chengqi Zhang

Files

Document Type

Book Contribution

Description/Summary

Haishuai Wang is a contirbuting author (with Peng Zhang, Ivor Tsang, Ling Chen, and Chengqi Zhang), "Defragging Subgraph Features for Graph Classification."

Conference Description:

The 24th ACM International Conference on Information and Knowledge Management (CIKM 2015) will be held from Oct 19-23, 2015 in Melbourne, Australia. CIKM is a top-tier ACM conference in the areas of information retrieval, knowledge management and databases. Since 1992, it has successfully brought together leading researchers and developers from the three communities, with the purpose of identifying challenging problems facing the development of advanced knowledge and information systems, and shaping future research directions through the publication of high quality, applied and theoretical research findings. With CIKM 2015, we will continue the tradition of promoting collaboration among multiple areas and are arranging an exciting program for the conference, including workshops, tutorials, industry speakers, keynote speakers, research papers, and posters.

Paper Abstract:

Graph classification is an important tool for analysing structured and semi-structured data, where subgraphs are commonly used as the feature representation. However, the number and size of subgraph features crucially depend on the threshold parameters of frequent subgraph mining algorithms. Any improper setting of the parameters will generate many trivial short-pattern subgraph fragments which dominate the feature space, distort graph classifiers and bury interesting long-pattern subgraphs. In this paper, we propose a new Subgraph Join Feature Selection (SJFS) algorithm. The SJFS algorithm, by forcing graph classifiers to join short-pattern subgraph fragments, can defrag trivial subgraph features and deliver long-pattern interesting subgraphs. Experimental results on both synthetic and real-world social network graph data demonstrate the performance of the proposed method.

ISBN

9781450337946

Publication Date

2015

Publication Information

Haishuai Wang, Peng Zhang, Ivor Tsang, Ling Chen, Chengqi Zhang. (2015). Defragging Subgraph Features for Graph Classification. CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management, ACM, pp.1687-1690.

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Copyright 2015 ACM

CIKM '15 Proceedings of the 24th ACM International on Conference on Information and Knowledge Management

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