TY - GEN
T1 - Ontology-based graph visualization for summarized view
AU - HUANG, Xin
AU - CHOI, Koon Kau
AU - XU, Jianliang
AU - CHEUNG, Kwok Wai
AU - Zhang, Yanchun
AU - LIU, Jiming
N1 - Funding Information:
Œis work was supported by the Hong Kong General Research Fund (GRF) Project Nos. HKBU 12200917, 12232716, 12200114, 12244916, and NSFC Grant No. 61672161.
PY - 2017/11/6
Y1 - 2017/11/6
N2 - 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 11?e 62%-approximation guarantee. Preliminary experimental results on real-world datasets show the effectiveness and efficiency of the proposed algorithm for data summarization.
AB - 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 11?e 62%-approximation guarantee. Preliminary experimental results on real-world datasets show the effectiveness and efficiency of the proposed algorithm for data summarization.
UR - http://www.scopus.com/inward/record.url?scp=85037330918&partnerID=8YFLogxK
U2 - 10.1145/3132847.3133113
DO - 10.1145/3132847.3133113
M3 - Conference proceeding
AN - SCOPUS:85037330918
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 2115
EP - 2118
BT - CIKM 2017 - Proceedings of the 2017 ACM Conference on Information and Knowledge Management
PB - Association for Computing Machinery (ACM)
T2 - 26th ACM International Conference on Information and Knowledge Management, CIKM 2017
Y2 - 6 November 2017 through 10 November 2017
ER -