TY - JOUR
T1 - HDAG-Explorer
T2 - A System for Hierarchical DAG Summarization and Exploration
AU - Zhu, Xuliang
AU - Huang, Xin
AU - Huang, Jinbin
AU - Choi, Byron Koon Kau
AU - Xu, Jianliang
N1 - Funding Information:
Acknowledgement. This paper is supported by NSFC 61702435, HK RGC GRF 12200917, 12201518, 12232716, HK RGC CRF C6030-18G, and Guangdong Basic and Applied Basic Research Foundation (Project No. 2019B1515130001). Xin Huang is the corresponding author.
Publisher Copyright:
© VLDB Endowment. All rights reserved.
PY - 2020/8
Y1 - 2020/8
N2 - Hierarchical directed acyclic graph (HDAG) is an essential graph model to represent terminology relationships in a hierarchy, such as Disease Ontology, Gene Ontology, and Wikipedia. However, due to massive terminologies and complex structures in a HDAG, an end user might feel difficult to explore and summarize the whole graph, which is practically useful but less studied in the literature. In this demo, we develop an interactive system of HDAG-Explorer to help users summarize HDAG with highly important and diverse vertices. Our HDAG-Explorer system exhibits several useful features including summarized visualization, interactive exploration, and structural statistics report. All these features facilitate in-depth understanding of the HDAG data. We showcase the usability of the HDAG-Explorer through two real-world applications of summarized topic recommendation and visual data exploration.
AB - Hierarchical directed acyclic graph (HDAG) is an essential graph model to represent terminology relationships in a hierarchy, such as Disease Ontology, Gene Ontology, and Wikipedia. However, due to massive terminologies and complex structures in a HDAG, an end user might feel difficult to explore and summarize the whole graph, which is practically useful but less studied in the literature. In this demo, we develop an interactive system of HDAG-Explorer to help users summarize HDAG with highly important and diverse vertices. Our HDAG-Explorer system exhibits several useful features including summarized visualization, interactive exploration, and structural statistics report. All these features facilitate in-depth understanding of the HDAG data. We showcase the usability of the HDAG-Explorer through two real-world applications of summarized topic recommendation and visual data exploration.
UR - http://vldb.org/pvldb/volumes/13/#issue-12
UR - http://www.scopus.com/inward/record.url?scp=85119103550&partnerID=8YFLogxK
U2 - 10.14778/3415478.3415522
DO - 10.14778/3415478.3415522
M3 - Journal article
AN - SCOPUS:85119103550
SN - 2150-8097
VL - 13
SP - 2973
EP - 2976
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
IS - 12
ER -