Icon placement regularization for Jammed profiles: Applications to web-registered personnel mining

Hiroyuki Kamiya, Ryota Yokote, Yasuo Matsuyama

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

    Abstract

    A new icon spotting method for designing a user-friendly GUI is described. Here, each icon can represent continuous and discrete vector data which are possibly high-dimensional. An important issue is icon-margin adjustment or uniforming while the relative positioning is maintained. For generating such GUI, multidimensional scaling, kernel principal component analysis (KPCA) and regularization were combined. This method was applied to a set of city locations and a big data set of web-registered job hunter profiles. The former is used to check to see location errors. There were only little mis-allocations. The latter is a set of high dimensional and sparsely discrete-valued big data in the real world. Through these experiments, it was recognized that the presented method, which combines multidimensional scaling, KPCA and the regularization, is applicable to a wide class of jammed big data for generating a user-friendly GUI.

    Original languageEnglish
    Title of host publicationCommunications in Computer and Information Science
    Pages70-79
    Number of pages10
    Volume409
    DOIs
    Publication statusPublished - 2013
    Event6th International Conference on Advances in Information Technology 2013, IAIT 2013 - Bangkok
    Duration: 2013 Dec 122013 Dec 13

    Publication series

    NameCommunications in Computer and Information Science
    Volume409
    ISSN (Print)18650929

    Other

    Other6th International Conference on Advances in Information Technology 2013, IAIT 2013
    CityBangkok
    Period13/12/1213/12/13

    Keywords

    • Data mining
    • GUI
    • Icon spotting
    • Regularization
    • Uniforming

    ASJC Scopus subject areas

    • Computer Science(all)

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  • Cite this

    Kamiya, H., Yokote, R., & Matsuyama, Y. (2013). Icon placement regularization for Jammed profiles: Applications to web-registered personnel mining. In Communications in Computer and Information Science (Vol. 409, pp. 70-79). (Communications in Computer and Information Science; Vol. 409). https://doi.org/10.1007/978-3-319-03783-7_7