Vizcs: Online searching and visualizing communities in dynamic graphs

Yuli Jiang; Xin HUANG; Hong Cheng; Jeffrey Xu Yu

doi:10.1109/ICDE.2018.00182

Vizcs: Online searching and visualizing communities in dynamic graphs

Yuli Jiang, Xin HUANG, Hong Cheng, Jeffrey Xu Yu

Department of Computer Science

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

9 Citations (Scopus)

Abstract

Given a query vertex in a graph, the task of community search is to find all meaningful communities containing the query vertex in an online manner. In this demonstration, we propose a novel query processing system for searching and visualizing communities in graphs, called VizCS. It exhibits three key innovative features. First, VizCS adopts several community models and supports community search on dynamic graphs where nodes/edges undergo frequently insertions/deletions. Second, VizCS offers a user-friendly visual interface to formulate queries and a real-Time response query processing engine. Last but not least, VizCS generates a community exploration wall by offering interactive community visualization, which facilitates users to in-depth understanding of the data. Furthermore, VizCS becomes a community search platform that can visualize and compare different community results by various state-of-The-Art algorithms and user-uploaded approaches.

Original language	English
Title of host publication	Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
Publisher	IEEE
Pages	1585-1588
Number of pages	4
ISBN (Electronic)	9781538655207
DOIs	https://doi.org/10.1109/ICDE.2018.00182
Publication status	Published - 24 Oct 2018
Event	34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France Duration: 16 Apr 2018 → 19 Apr 2018 https://ieeexplore.ieee.org/xpl/conhome/8476188/proceeding

Publication series

Name	Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Conference

Conference	34th IEEE International Conference on Data Engineering, ICDE 2018
Country/Territory	France
City	Paris
Period	16/04/18 → 19/04/18
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8476188/proceeding

Scopus Subject Areas

Information Systems
Information Systems and Management
Hardware and Architecture

User-Defined Keywords

COMMUNITY SEARCH
K-TRUSS
ONLINE SEARCH

Access to Document

10.1109/ICDE.2018.00182

Cite this

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title = "Vizcs: Online searching and visualizing communities in dynamic graphs",

abstract = "Given a query vertex in a graph, the task of community search is to find all meaningful communities containing the query vertex in an online manner. In this demonstration, we propose a novel query processing system for searching and visualizing communities in graphs, called VizCS. It exhibits three key innovative features. First, VizCS adopts several community models and supports community search on dynamic graphs where nodes/edges undergo frequently insertions/deletions. Second, VizCS offers a user-friendly visual interface to formulate queries and a real-Time response query processing engine. Last but not least, VizCS generates a community exploration wall by offering interactive community visualization, which facilitates users to in-depth understanding of the data. Furthermore, VizCS becomes a community search platform that can visualize and compare different community results by various state-of-The-Art algorithms and user-uploaded approaches.",

keywords = "COMMUNITY SEARCH, K-TRUSS, ONLINE SEARCH",

author = "Yuli Jiang and Xin HUANG and Hong Cheng and Yu, {Jeffrey Xu}",

note = "Funding Information: ACKNOWLEDGMENT This work was supported by grants from the Research Grants Council of the Hong Kong Special Administratvi e Region, China [Project No.: CUHK 14205617], [Project No.: CUHK 14221716], and [Project No.: HKBU 12200917].; 34th IEEE International Conference on Data Engineering, ICDE 2018 ; Conference date: 16-04-2018 Through 19-04-2018",

year = "2018",

month = oct,

day = "24",

doi = "10.1109/ICDE.2018.00182",

language = "English",

series = "Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018",

publisher = "IEEE",

pages = "1585--1588",

booktitle = "Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018",

address = "United States",

url = "https://ieeexplore.ieee.org/xpl/conhome/8476188/proceeding",

}

Jiang, Y, HUANG, X, Cheng, H & Yu, JX 2018, Vizcs: Online searching and visualizing communities in dynamic graphs. in Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018., 8509403, Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018, IEEE, pp. 1585-1588, 34th IEEE International Conference on Data Engineering, ICDE 2018, Paris, France, 16/04/18. https://doi.org/10.1109/ICDE.2018.00182

Vizcs : Online searching and visualizing communities in dynamic graphs. / Jiang, Yuli; HUANG, Xin; Cheng, Hong et al.

Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018. IEEE, 2018. p. 1585-1588 8509403 (Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018).

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

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T2 - 34th IEEE International Conference on Data Engineering, ICDE 2018

AU - Jiang, Yuli

AU - HUANG, Xin

AU - Cheng, Hong

AU - Yu, Jeffrey Xu

N1 - Funding Information: ACKNOWLEDGMENT This work was supported by grants from the Research Grants Council of the Hong Kong Special Administratvi e Region, China [Project No.: CUHK 14205617], [Project No.: CUHK 14221716], and [Project No.: HKBU 12200917].

PY - 2018/10/24

Y1 - 2018/10/24

N2 - Given a query vertex in a graph, the task of community search is to find all meaningful communities containing the query vertex in an online manner. In this demonstration, we propose a novel query processing system for searching and visualizing communities in graphs, called VizCS. It exhibits three key innovative features. First, VizCS adopts several community models and supports community search on dynamic graphs where nodes/edges undergo frequently insertions/deletions. Second, VizCS offers a user-friendly visual interface to formulate queries and a real-Time response query processing engine. Last but not least, VizCS generates a community exploration wall by offering interactive community visualization, which facilitates users to in-depth understanding of the data. Furthermore, VizCS becomes a community search platform that can visualize and compare different community results by various state-of-The-Art algorithms and user-uploaded approaches.

AB - Given a query vertex in a graph, the task of community search is to find all meaningful communities containing the query vertex in an online manner. In this demonstration, we propose a novel query processing system for searching and visualizing communities in graphs, called VizCS. It exhibits three key innovative features. First, VizCS adopts several community models and supports community search on dynamic graphs where nodes/edges undergo frequently insertions/deletions. Second, VizCS offers a user-friendly visual interface to formulate queries and a real-Time response query processing engine. Last but not least, VizCS generates a community exploration wall by offering interactive community visualization, which facilitates users to in-depth understanding of the data. Furthermore, VizCS becomes a community search platform that can visualize and compare different community results by various state-of-The-Art algorithms and user-uploaded approaches.

KW - COMMUNITY SEARCH

KW - K-TRUSS

KW - ONLINE SEARCH

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BT - Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

PB - IEEE

Y2 - 16 April 2018 through 19 April 2018

ER -

Vizcs: Online searching and visualizing communities in dynamic graphs

Abstract

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Scopus Subject Areas

User-Defined Keywords

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