FGreat: Focused graph query autocompletion

Nathan Ng; Peipei Yi; Zhiwei Zhang; Koon Kau Choi; Sourav S. Bhowmick; Jianliang Xu

doi:10.1109/ICDE.2019.00213

FGreat: Focused graph query autocompletion

Nathan Ng
, Peipei Yi
, Zhiwei Zhang
, Koon Kau Choi
, Sourav S. Bhowmick
, Jianliang Xu

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

2 Citations (Scopus)

Abstract

Composing queries is evidently a tedious task. This is particularly true of graph queries as they are typically complex and prone to errors. This is compounded by the fact that graph schemas can be missing or too loose to be helpful for query formulation. Graph Query AutoCompletion (gQAC) alleviates users from the potentially painstaking task of graph query formulation. This demonstration presents an interactive visual Focused GRaph quEry AutocompleTion framework, called FGreat. Its novelty relies on the user focus for gQAC, which is a subgraph of the current query that a user is focusing on. FGreat automatically computes a focus and completes the query at the focus, as opposed to an arbitrary query subgraph. This demonstration presents two complementary approaches to compute the user focus for different circumstances. It computes the focus from either (i) the sequence of edges that a user recently added to his/her query, or (ii) the position of the mouse cursor, if it is available. We demonstrate that the user focus enhances both the effectiveness and efficiency of graph query autocompletion.

Original language	English
Title of host publication	Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019
Publisher	IEEE Computer Society
Pages	1956-1959
Number of pages	4
ISBN (Electronic)	9781538674741
DOIs	https://doi.org/10.1109/ICDE.2019.00213
Publication status	Published - Apr 2019
Event	35th IEEE International Conference on Data Engineering, ICDE 2019 - Macau, China Duration: 8 Apr 2019 → 11 Apr 2019 https://doi.org/10.1109/ICDE44378.2019 (Conference proceedings)

Publication series

Name	Proceedings - International Conference on Data Engineering
Volume	2019-April
ISSN (Print)	1084-4627

Conference

Conference	35th IEEE International Conference on Data Engineering, ICDE 2019
Abbreviated title	ICDE 2019
Country/Territory	China
City	Macau
Period	8/04/19 → 11/04/19
Internet address	https://doi.org/10.1109/ICDE44378.2019 (Conference proceedings)

User-Defined Keywords

Database usability
Graph autocompletion
Graphs
Subgraph query

Access to Document

10.1109/ICDE.2019.00213

Cite this

Ng, N., Yi, P., Zhang, Z., Choi, K. K., Bhowmick, S. S., & Xu, J. (2019). FGreat: Focused graph query autocompletion. In Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019 (pp. 1956-1959). Article 8731451 (Proceedings - International Conference on Data Engineering; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.1109/ICDE.2019.00213

@inproceedings{e0a95e3130ae4b89b56022c43d6a3fde,

title = "FGreat: Focused graph query autocompletion",

abstract = "Composing queries is evidently a tedious task. This is particularly true of graph queries as they are typically complex and prone to errors. This is compounded by the fact that graph schemas can be missing or too loose to be helpful for query formulation. Graph Query AutoCompletion (gQAC) alleviates users from the potentially painstaking task of graph query formulation. This demonstration presents an interactive visual Focused GRaph quEry AutocompleTion framework, called FGreat. Its novelty relies on the user focus for gQAC, which is a subgraph of the current query that a user is focusing on. FGreat automatically computes a focus and completes the query at the focus, as opposed to an arbitrary query subgraph. This demonstration presents two complementary approaches to compute the user focus for different circumstances. It computes the focus from either (i) the sequence of edges that a user recently added to his/her query, or (ii) the position of the mouse cursor, if it is available. We demonstrate that the user focus enhances both the effectiveness and efficiency of graph query autocompletion.",

keywords = "Database usability, Graph autocompletion, Graphs, Subgraph query",

author = "Nathan Ng and Peipei Yi and Zhiwei Zhang and Choi, \{Koon Kau\} and Bhowmick, \{Sourav S.\} and Jianliang Xu",

note = "Funding Information: Finally, the attendees can observe the suggestion characteristics by tuning system parameters (e.g., α, β and k). A demonstration video is publicly available at https://goo.gl/gX6LSn. Acknowledgments. This work was partially supported by AcRF MOE2015-T2-1-040, NSFC 61602395, and HKRGC GRF12232716, 12201315, 12201518, and 12258116. Mr. Ng visited NTU in Jun-July 2017 under the UG overseas summer research scholarship of Dept. of CS at HKBU.; 35th IEEE International Conference on Data Engineering, ICDE 2019, ICDE 2019 ; Conference date: 08-04-2019 Through 11-04-2019",

year = "2019",

month = apr,

doi = "10.1109/ICDE.2019.00213",

language = "English",

series = "Proceedings - International Conference on Data Engineering",

publisher = "IEEE Computer Society",

pages = "1956--1959",

booktitle = "Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019",

address = "United States",

url = "https://doi.org/10.1109/ICDE44378.2019",

}

Ng, N, Yi, P, Zhang, Z, Choi, KK, Bhowmick, SS & Xu, J 2019, FGreat: Focused graph query autocompletion. in Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019., 8731451, Proceedings - International Conference on Data Engineering, vol. 2019-April, IEEE Computer Society, pp. 1956-1959, 35th IEEE International Conference on Data Engineering, ICDE 2019, Macau, China, 8/04/19. https://doi.org/10.1109/ICDE.2019.00213

FGreat: Focused graph query autocompletion. / Ng, Nathan; Yi, Peipei; Zhang, Zhiwei et al.
Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019. IEEE Computer Society, 2019. p. 1956-1959 8731451 (Proceedings - International Conference on Data Engineering; Vol. 2019-April).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - FGreat

T2 - 35th IEEE International Conference on Data Engineering, ICDE 2019

AU - Ng, Nathan

AU - Yi, Peipei

AU - Zhang, Zhiwei

AU - Choi, Koon Kau

AU - Bhowmick, Sourav S.

AU - Xu, Jianliang

N1 - Funding Information: Finally, the attendees can observe the suggestion characteristics by tuning system parameters (e.g., α, β and k). A demonstration video is publicly available at https://goo.gl/gX6LSn. Acknowledgments. This work was partially supported by AcRF MOE2015-T2-1-040, NSFC 61602395, and HKRGC GRF12232716, 12201315, 12201518, and 12258116. Mr. Ng visited NTU in Jun-July 2017 under the UG overseas summer research scholarship of Dept. of CS at HKBU.

PY - 2019/4

Y1 - 2019/4

N2 - Composing queries is evidently a tedious task. This is particularly true of graph queries as they are typically complex and prone to errors. This is compounded by the fact that graph schemas can be missing or too loose to be helpful for query formulation. Graph Query AutoCompletion (gQAC) alleviates users from the potentially painstaking task of graph query formulation. This demonstration presents an interactive visual Focused GRaph quEry AutocompleTion framework, called FGreat. Its novelty relies on the user focus for gQAC, which is a subgraph of the current query that a user is focusing on. FGreat automatically computes a focus and completes the query at the focus, as opposed to an arbitrary query subgraph. This demonstration presents two complementary approaches to compute the user focus for different circumstances. It computes the focus from either (i) the sequence of edges that a user recently added to his/her query, or (ii) the position of the mouse cursor, if it is available. We demonstrate that the user focus enhances both the effectiveness and efficiency of graph query autocompletion.

AB - Composing queries is evidently a tedious task. This is particularly true of graph queries as they are typically complex and prone to errors. This is compounded by the fact that graph schemas can be missing or too loose to be helpful for query formulation. Graph Query AutoCompletion (gQAC) alleviates users from the potentially painstaking task of graph query formulation. This demonstration presents an interactive visual Focused GRaph quEry AutocompleTion framework, called FGreat. Its novelty relies on the user focus for gQAC, which is a subgraph of the current query that a user is focusing on. FGreat automatically computes a focus and completes the query at the focus, as opposed to an arbitrary query subgraph. This demonstration presents two complementary approaches to compute the user focus for different circumstances. It computes the focus from either (i) the sequence of edges that a user recently added to his/her query, or (ii) the position of the mouse cursor, if it is available. We demonstrate that the user focus enhances both the effectiveness and efficiency of graph query autocompletion.

KW - Database usability

KW - Graph autocompletion

KW - Graphs

KW - Subgraph query

UR - https://www.scopus.com/pages/publications/85067987815

U2 - 10.1109/ICDE.2019.00213

DO - 10.1109/ICDE.2019.00213

M3 - Conference proceeding

AN - SCOPUS:85067987815

T3 - Proceedings - International Conference on Data Engineering

SP - 1956

EP - 1959

BT - Proceedings - 2019 IEEE 35th International Conference on Data Engineering, ICDE 2019

PB - IEEE Computer Society

Y2 - 8 April 2019 through 11 April 2019

ER -

FGreat: Focused graph query autocompletion

Abstract

Publication series

Conference

User-Defined Keywords

Access to Document

Other files and links

Fingerprint

Cite this