Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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 ighted 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 ll as visualization tool sub-optimal or even mis-leading. ,  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.  formulate this as a multi-objective feature selection problem, and propose an integrated framework, BrainQuest, to solve it.  perform extensive empirical evaluations, both quantitatively and qualitatively, to demonstrate the effectiveness and efficiency of our approach.
['Lei Shi', 'Hanghang Tong', 'Xinzhu Mu']
I am writing a research paper on a idea BrainQuest: Perception-Guided Brain Network Comparison
[{"from": "human", "value": "I am writing a research paper on a idea BrainQuest: Perception-Guided Brain Network Comparison"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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 ighted 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 ll as visualization tool sub-optimal or even mis-leading. ,  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.  formulate this as a multi-objective feature selection problem, and propose an integrated framework, BrainQuest, to solve it.  perform extensive empirical evaluations, both quantitatively and qualitatively, to demonstrate the effectiveness and efficiency of our approach."}]