Abstract: In a display area of a display, a KPT screen in which a theme area, a keep area (Keep), a problem area (Problem), and a try area (Try) are disposed is displayed. When a click of the area is detected, a new generation menu of an article corresponding to the area is displayed so as to enable an editing operation of new generation of an article by menu selection. When a click of an article display which is displayed in a tag image in the problem area is detected, new generation menus of articles of the other areas are displayed in addition to a correction menu and a deletion menu of the specified article, so as to enable new generation of an article of another area, for example, the try area in association with the clicked article display.

Abstract: A policy management program, a policy management apparatus and a policy management method can evaluate policies. A policy management program causes a computer to manage the policies in a project by causing the computer to execute a policy registration step that registers policy information including the contents of policies, a first evaluation step that acquires case information satisfying the predetermined first requirement from the case information including the contents of the utilized policies registered in advance and computationally determines an evaluation value for each of the policies registered in the policy registration step according to the case information and a display step that displays the policy information of the one or more than one policies showing an evaluation value satisfying the predetermined second requirement as computed in the first evaluation step.

Abstract: This invention is to automatically carry out the retracement of the knowledge. Therefore, this method is executed by a computer having a retracement data storage storing a target type of a past project, data concerning a scale of the past project, a specific phase of the past project, data concerning a problem in the specific phase of the past project, and data concerning an action against a problem in the specific phase of the past project.

Abstract: This invention is to automatically carry out the retracement of the knowledge. Therefore, this method is executed by a computer having a retracement data storage storing a target type of a past project, data concerning a scale of the past project, a specific phase of the past project, data concerning a problem in the specific phase of the past project, and data concerning an action against a problem in the specific phase of the past project.

Abstract: The information use frequency prediction device is provided with a comparison section for shifting a second time series data related to the use frequency of a first keyword, sequentially on the time base in a unit of predetermined time, based on a first time series data related to the use frequency of a second keyword input while searching over the Internet, and calculating a correlation coefficient between the first time series data and the second time series data, for each unit of predetermined time. Moreover, a prediction section specifies a pair of the first time series data and the second time series data, corresponding to the correlation coefficient having the highest value, of a plurality of correlation coefficients calculated by the comparison section and for predicting the use frequency of the first time series data constituting the pair, based on the second time series data.

Abstract: The information use frequency prediction device is provided with a comparison section for shifting a second time series data related to the use frequency of a first keyword, sequentially on the time base in a unit of predetermined time, based on a first time series data related to the use frequency of a second keyword input while searching over the Internet, and calculating a correlation coefficient between the first time series data and the second time series data, for each unit of predetermined time. Moreover, a prediction section specifies a pair of the first time series data and the second time series data, corresponding to the correlation coefficient having the highest value, of a plurality of correlation coefficients calculated by the comparison section and for predicting the use frequency of the first time series data constituting the pair, based on the second time series data.