G-Miner: Interactive visual group mining on multivariate graphs

Nan Cao, Yu Ru Lin, Liangyue Li, Hanghang Tong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

27 Citations (Scopus)

Abstract

With the rapid growth of rich network data available through various sources such as social media and digital archives, there is a growing interest in more powerful network visual analysis tools and methods. The rich information about the network nodes and links can be represented as multivariate graphs, in which the nodes are accompanied with attributes to represent the properties of individual nodes. An important task often encountered in multivariate network analysis is to uncover link structure with groups, e.g., to understand why a person fits a specific job or certain role in a social group well. The task usually involves complex considerations including specific requirement of node attributes and link structure, and hence a fully automatic solution is typically not satisfactory. In this work, we identify the design challenges for mining groups with complex criteria and present an interactive system, "g-Miner," that enables visual mining of groups on multivariate graph data. We demonstrate the effectiveness of our system through case study and in-depth expert interviews. This work contributes to understanding the design of systems for leveraging users' knowledge progressively with algorithmic capacity for tackling massive heterogeneous information.

Original languageEnglish (US)
Title of host publicationConference on Human Factors in Computing Systems - Proceedings
PublisherAssociation for Computing Machinery
Pages279-288
Number of pages10
Volume2015-April
ISBN (Print)9781450331456
DOIs
StatePublished - Apr 18 2015
Event33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015 - Seoul, Korea, Republic of
Duration: Apr 18 2015Apr 23 2015

Other

Other33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015
CountryKorea, Republic of
CitySeoul
Period4/18/154/23/15

Fingerprint

Miners
Electric network analysis

Keywords

  • Group mining
  • Information visualization
  • Visual analysis

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design
  • Software

Cite this

Cao, N., Lin, Y. R., Li, L., & Tong, H. (2015). G-Miner: Interactive visual group mining on multivariate graphs. In Conference on Human Factors in Computing Systems - Proceedings (Vol. 2015-April, pp. 279-288). Association for Computing Machinery. https://doi.org/10.1145/2702123.2702446

G-Miner : Interactive visual group mining on multivariate graphs. / Cao, Nan; Lin, Yu Ru; Li, Liangyue; Tong, Hanghang.

Conference on Human Factors in Computing Systems - Proceedings. Vol. 2015-April Association for Computing Machinery, 2015. p. 279-288.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Cao, N, Lin, YR, Li, L & Tong, H 2015, G-Miner: Interactive visual group mining on multivariate graphs. in Conference on Human Factors in Computing Systems - Proceedings. vol. 2015-April, Association for Computing Machinery, pp. 279-288, 33rd Annual CHI Conference on Human Factors in Computing Systems, CHI 2015, Seoul, Korea, Republic of, 4/18/15. https://doi.org/10.1145/2702123.2702446
Cao N, Lin YR, Li L, Tong H. G-Miner: Interactive visual group mining on multivariate graphs. In Conference on Human Factors in Computing Systems - Proceedings. Vol. 2015-April. Association for Computing Machinery. 2015. p. 279-288 https://doi.org/10.1145/2702123.2702446
Cao, Nan ; Lin, Yu Ru ; Li, Liangyue ; Tong, Hanghang. / G-Miner : Interactive visual group mining on multivariate graphs. Conference on Human Factors in Computing Systems - Proceedings. Vol. 2015-April Association for Computing Machinery, 2015. pp. 279-288
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