Department of Computer Science
Ontology-based graph visualization for summarized view
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.
Source Publication Title
CIKM'17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
The Association for Computing Machinery
© 2017 ACM
Link to Publisher's Edition
Huang, Xin, Byron Choi, Jianliang Xu, William K. Cheung, Yanchun Zhang, and Jiming Liu. "Ontology-based graph visualization for summarized view." CIKM'17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management (2017): 2115-2118.