TY - GEN
T1 - Composite data mapping for spherical GUI design
T2 - 19th International Conference on Neural Information Processing, ICONIP 2012
AU - Maejima, Masaya
AU - Yokote, Ryota
AU - Matsuyama, Yasuo
PY - 2012
Y1 - 2012
N2 - Mapping tools applicable to big data of composite elements are designed based on a machine learning approach. The central method adopted is the multi-dimensional scaling (MDS). The data set is mapped onto a continuous surface such as a sphere. For checking to see the effectiveness of this method, preliminary experiments on the local optimality were conducted. Supported by those results, the main target for the application in this paper is the design for a spherical GUI (Graphical User Interface) which presents "must-watch" and "no-need" program clusters in TV big data. This GUI shows a certain genre of programs at around the North Pole. Programs having an opposite genre placed at around the South Pole. Since all-recording systems of TV programs are within the realm of home appliances, this GUI can be expected to be one of necessary tools for a video culture.
AB - Mapping tools applicable to big data of composite elements are designed based on a machine learning approach. The central method adopted is the multi-dimensional scaling (MDS). The data set is mapped onto a continuous surface such as a sphere. For checking to see the effectiveness of this method, preliminary experiments on the local optimality were conducted. Supported by those results, the main target for the application in this paper is the design for a spherical GUI (Graphical User Interface) which presents "must-watch" and "no-need" program clusters in TV big data. This GUI shows a certain genre of programs at around the North Pole. Programs having an opposite genre placed at around the South Pole. Since all-recording systems of TV programs are within the realm of home appliances, this GUI can be expected to be one of necessary tools for a video culture.
KW - big data
KW - Clustering
KW - GUI design
KW - multi-dimensional scaling
KW - TV programs
UR - http://www.scopus.com/inward/record.url?scp=84869072395&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869072395&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34500-5_32
DO - 10.1007/978-3-642-34500-5_32
M3 - Conference contribution
AN - SCOPUS:84869072395
SN - 9783642344992
VL - 7667 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 267
EP - 274
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Y2 - 12 November 2012 through 15 November 2012
ER -