Presentation 2019-03-07
Efficient Search Method for Best Combination of Multiple Action Plans
Masahiko Yasui, Atsushi Tomoda, Masashi Egi,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In data analysis, conditions that are effective for KPI are extracted and multiple actions are planned. However, when executing multiple action plans at the same time, because of the intersection between their targets, it is not the most effective for KPI to execute the combination of action plans which have the best score. For the search method for best combination of multiple action plans, all combinations of action plans must be considered in the worst case, and calculation cost was a problem. In this research, we propose a method to reduce the calculation cost by efficient search method using novel defined upward compatibility among action plans. We applied the proposed method to the data of academic achievement and evaluate the calculation cost. As a result, we reduced calculation cost by 60 percent.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Data Analytics / Decision Making Support
Paper # LOIS2018-65
Date of Issue 2019-02-28 (LOIS)

Conference Information
Committee LOIS
Conference Date 2019/3/7(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Miyakojima-shi Central Community Center
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Tomohiro Yamada(NTT)
Vice Chair Toru Kobayashi(Nagasaki Univ.)
Secretary Toru Kobayashi(NTT)
Assistant Shinichiro Eitoku(NTT)

Paper Information
Registration To Technical Committee on Life Intelligence and Office Information Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Efficient Search Method for Best Combination of Multiple Action Plans
Sub Title (in English)
Keyword(1) Data Analytics
Keyword(2) Decision Making Support
1st Author's Name Masahiko Yasui
1st Author's Affiliation Hitachi, Ltd.(Hitachi)
2nd Author's Name Atsushi Tomoda
2nd Author's Affiliation Hitachi, Ltd.(Hitachi)
3rd Author's Name Masashi Egi
3rd Author's Affiliation Hitachi, Ltd.(Hitachi)
Date 2019-03-07
Paper # LOIS2018-65
Volume (vol) vol.118
Number (no) LOIS-485
Page pp.pp.57-60(LOIS),
#Pages 4
Date of Issue 2019-02-28 (LOIS)