@inproceedings{5c69b766b62b4d518d48320352129b20,
title = "An indexing framework for efficient visual exploratory subgraph search in graph databases",
abstract = "Although exploratory search has received significant attention recently in the context of structured data, scant attention has been paid for graph-structured data. In this paper, we present two novel index structures called VACCINE and ADVISE to efficiently support exploratory subgraph search in a visual environment (VESS). VACCINE is an offline, feature-based index that stores rich information related to frequent and infrequent subgraphs in the underlying graph database and how they can be transformed from one subgraph to another. ADVISE, on the other hand, is an adaptive, compact, on-the-fly index instantiated during iterative visual formulation/reformulation of a subgraph query for exploratory search and records relevant information to efficiently support its repeated evaluation. These indexes engender more efficient and scalable visual exploratory subgraph search framework compared to a state-of-the-art technique.",
keywords = "Exploratory search, Graph database, Indexing, Visual interface",
author = "Chaohui Wang and Miao Xie and Bhowmick, {Sourav S.} and CHOI, {Koon Kau} and Xiaokui Xiao and Shuigeng Zhou",
note = "Funding Information: Acknowledgments. The first three authors are supported by AcRF MOE2015-T2-1-040 and AcRF Tier-1 Grant RG24/12. Shuigeng Zhou is supported by National NSF of China (grant No. U1636205).; 35th IEEE International Conference on Data Engineering, ICDE 2019 ; Conference date: 08-04-2019 Through 11-04-2019",
year = "2019",
month = apr,
doi = "10.1109/ICDE.2019.00168",
language = "English",
series = "Proceedings - International Conference on Data Engineering",
publisher = "IEEE Computer Society",
pages = "1666--1669",
booktitle = "Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019",
address = "United States",
}
