INTERVENTION SYSTEM, INTERVENTION METHOD, AND INTERVENTION PROGRAM

• Main Authors: TANAKA TAKESHI, LI ZISHENG, SANO YUKO, OGINO MASAHIRO
• Format: Patent
• Language: English; Japanese
• Published: 07.10.2022
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

To provide a system for proposing an improvement content to increase activity productivity of an object person after presenting an intervention effect.SOLUTION: An intervention system performs intervention for proposing an improvement content of a factor having an influence on an object person to the object person and/or a user in order to improve the activity productivity of the object person. First, the system measures a value representing a feature amount about one or more influence factors to have an influence on the object person, accepts input of the value in a learning model, and acquires a prediction value of activity productivity to be outputted by the learning model as a prediction result without intervention. Next, the system accepts input of an improvement content of a feature amount created in advance and a value representing the feature amount in the learning model, and acquires a prediction result with intervention to be outputted by the learning model. The system calculates a difference between the prediction result without intervention and the prediction result with intervention as an intervention effect, and notifies the object person of the difference in association with the improvement content.SELECTED DRAWING: Figure 11 【課題】介入効果を提示した上で、対象者の活動生産性を高めるための改善内容を提案するシステムを提供する。【解決手段】対象者の活動生産性を向上させるために、対象者に影響を与える要因の改善内容を対象者および／またはユーザーに提案する介入を行う。まず、対象者に影響を与える１以上の影響要因について特徴量を表す値を計測し、学習モデルに入力し、学習モデルが出力する活動生産性の予測値を介入なし予測結果として取得する。つぎに、予め作成しておいた特徴量の改善内容と、特徴量を表す値とを、学習モデルに入力し、学習モデルが出力する介入あり予測結果を取得する。介入なし予測結果と、介入あり予測結果との差分を、介入効果として算出し、改善内容と対応させて対象者に通知する。【選択図】図１１