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
Matlamat kerja ini adalah untuk membangunkan kaedah untuk analisis serentak beberapa kumpulan dan ahli mereka berdasarkan pemodelan manifold tensor hierarki. Kaedah ini direka khusus untuk menganalisis berbilang pasukan, seperti pasukan sukan dan pasukan perniagaan. Kaedah yang dicadangkan mewakili data ahli menggunakan manifold tak linear untuk setiap pasukan, dan kemudian manifold ini selanjutnya dimodelkan menggunakan manifold tak linear lain dalam ruang model. Untuk tujuan ini, kaedah menganggarkan peranan setiap ahli dalam pasukan, dan menemui surat-menyurat antara ahli yang memainkan peranan yang serupa dalam pasukan yang berbeza. Kaedah yang dicadangkan telah digunakan untuk data liga bola keranjang, dan ia menunjukkan keupayaan penemuan pengetahuan daripada statistik pemain. Kami juga menunjukkan bahawa kaedah itu boleh digunakan sebagai alat umum untuk analisis berbilang kumpulan berbilang peringkat dengan menggunakannya pada data pemasaran.
Hideaki ISHIBASHI
the Institute of Statistical Mathematics
Masayoshi ERA
Kyushu Institute of Technology
Tetsuo FURUKAWA
Kyushu Institute of Technology
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Salinan
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
Salinan
@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},}
Salinan
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 -