Abstract
Classic part-labeled data visualization method Parallel Sets is applied to represent visualization of multivariate data with measures. Currently, in all walks of life emerge abundant small records and documents. Thus to sort the massive categorical measures of small value on the variable axis plays an important role in reducing clutters in the view. This paper is based on the Advanced Categories Layout basEd on Average heuRistic with Cardinality Reduction (ACLEARCR), and proposes an optimization sequence algorithm aiming at categorical measures of small value. The case study proves that the proposed method is effective.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
