BrainQuest: Perception-guided brain network comparison

Lei Shi, Hanghang Tong, Xinzhu Mu

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

6 Scopus citations


Why are some people more creative than others? How do human brain networks evolve over time? A key stepping stone to both mysteries and many more is to compare weighted brain networks. In contrast to networks arising from other application domains, the brain network exhibits its own characteristics (e.g., high density, indistinguishability), which makes any off-the-shelf data mining algorithm as well as visualization tool sub-optimal or even mis-leading. In this paper, we propose a shift from the current mining-then-visualization paradigm, to jointly model these two core building blocks (i.e., mining and visualization) for brain network comparisons. The key idea is to integrate the human perception constraint into the mining block earlier so as to guide the analysis process. We formulate this as a multi-objective feature selection problem, and propose an integrated framework, BrainQuest, to solve it. We perform extensive empirical evaluations, both quantitatively and qualitatively, to demonstrate the effectiveness and efficiency of our approach.

Original languageEnglish (US)
Title of host publicationProceedings - 15th IEEE International Conference on Data Mining, ICDM 2015
EditorsCharu Aggarwal, Zhi-Hua Zhou, Alexander Tuzhilin, Hui Xiong, Xindong Wu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages10
ISBN (Electronic)9781467395038
StatePublished - Jan 5 2016
Event15th IEEE International Conference on Data Mining, ICDM 2015 - Atlantic City, United States
Duration: Nov 14 2015Nov 17 2015

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786


Other15th IEEE International Conference on Data Mining, ICDM 2015
Country/TerritoryUnited States
CityAtlantic City

ASJC Scopus subject areas

  • General Engineering


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