Document Type

Conference Paper

Department/Unit

Department of Computer Science

Title

Ontology-based graph visualization for summarized view

Language

English

Abstract

Data summarization that presents a small subset of a dataset to users has been widely applied in numerous applications and systems. Many datasets are coded with hierarchical terminologies, e.g., the international classification of Diseases-9, Medical Subject Heading, and Gene Ontology, to name a few. In this paper, we study the problem of selecting a diverse set of k elements to summarize an input dataset with hierarchical terminologies, and visualize the summary in an ontology structure. We propose an efficient greedy algorithm to solve the problem with (1-1/e)≈ 62%-approximation guarantee. Preliminary experimental results on real-world datasets show the effectiveness and efficiency of the proposed algorithm for data summarization.

Publication Date

11-2017

Source Publication Title

CIKM'17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Start Page

2115

End Page

2118

Conference Location

Singapore

Publisher

The Association for Computing Machinery

Copyright

© 2017 ACM

DOI

10.1145/3132847.3133113

Link to Publisher's Edition

http://dx.doi.org/10.1145/3132847.3133113

ISBN (print)

9781450349185

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