The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
O objetivo deste trabalho é desenvolver um método para a análise simultânea de múltiplos grupos e seus membros baseado na modelagem hierárquica de variedades tensoriais. O método é especialmente projetado para analisar múltiplas equipes, como equipes esportivas e equipes empresariais. O método proposto representa os dados dos membros usando uma variedade não linear para cada equipe, e então essas variedades são posteriormente modeladas usando outra variedade não linear no espaço do modelo. Para tanto, o método estima o papel de cada membro da equipe e descobre correspondências entre membros que desempenham funções semelhantes em equipes diferentes. O método proposto foi aplicado a dados de ligas de basquete e demonstrou a capacidade de descoberta de conhecimento a partir de estatísticas dos jogadores. Também demonstramos que o método poderia ser usado como uma ferramenta geral para análise multinível e multigrupo, aplicando-o a dados de marketing.
Hideaki ISHIBASHI
the Institute of Statistical Mathematics
Masayoshi ERA
Kyushu Institute of Technology
Tetsuo FURUKAWA
Kyushu Institute of Technology
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Hideaki ISHIBASHI, Masayoshi ERA, Tetsuo FURUKAWA, "Hierarchical Tensor Manifold Modeling for Multi-Group Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E101-A, no. 11, pp. 1745-1755, November 2018, doi: 10.1587/transfun.E101.A.1745.
Abstract: The aim of this work is to develop a method for the simultaneous analysis of multiple groups and their members based on hierarchical tensor manifold modeling. The method is particularly designed to analyze multiple teams, such as sports teams and business teams. The proposed method represents members' data using a nonlinear manifold for each team, and then these manifolds are further modeled using another nonlinear manifold in the model space. For this purpose, the method estimates the role of each member in the team, and discovers correspondences between members that play similar roles in different teams. The proposed method was applied to basketball league data, and it demonstrated the ability of knowledge discovery from players' statistics. We also demonstrated that the method could be used as a general tool for multi-level multi-group analysis by applying it to marketing data.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E101.A.1745/_p
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@ARTICLE{e101-a_11_1745,
author={Hideaki ISHIBASHI, Masayoshi ERA, Tetsuo FURUKAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Hierarchical Tensor Manifold Modeling for Multi-Group Analysis},
year={2018},
volume={E101-A},
number={11},
pages={1745-1755},
abstract={The aim of this work is to develop a method for the simultaneous analysis of multiple groups and their members based on hierarchical tensor manifold modeling. The method is particularly designed to analyze multiple teams, such as sports teams and business teams. The proposed method represents members' data using a nonlinear manifold for each team, and then these manifolds are further modeled using another nonlinear manifold in the model space. For this purpose, the method estimates the role of each member in the team, and discovers correspondences between members that play similar roles in different teams. The proposed method was applied to basketball league data, and it demonstrated the ability of knowledge discovery from players' statistics. We also demonstrated that the method could be used as a general tool for multi-level multi-group analysis by applying it to marketing data.},
keywords={},
doi={10.1587/transfun.E101.A.1745},
ISSN={1745-1337},
month={November},}
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TY - JOUR
TI - Hierarchical Tensor Manifold Modeling for Multi-Group Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1745
EP - 1755
AU - Hideaki ISHIBASHI
AU - Masayoshi ERA
AU - Tetsuo FURUKAWA
PY - 2018
DO - 10.1587/transfun.E101.A.1745
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E101-A
IS - 11
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - November 2018
AB - The aim of this work is to develop a method for the simultaneous analysis of multiple groups and their members based on hierarchical tensor manifold modeling. The method is particularly designed to analyze multiple teams, such as sports teams and business teams. The proposed method represents members' data using a nonlinear manifold for each team, and then these manifolds are further modeled using another nonlinear manifold in the model space. For this purpose, the method estimates the role of each member in the team, and discovers correspondences between members that play similar roles in different teams. The proposed method was applied to basketball league data, and it demonstrated the ability of knowledge discovery from players' statistics. We also demonstrated that the method could be used as a general tool for multi-level multi-group analysis by applying it to marketing data.
ER -