FFM-based situation information classification recommendation system and method under multi-task condition

Abstract

The invention discloses an FFM-based situation information classification recommendation system and method under a multi-task condition. The method comprises the following steps: establishing a Pew-based task processing model, analyzing current task state information, calculating task completion probabilities under different situation information recommendation strategies by utilizing an FFM model according to different attention degrees of different tasks on different situation information and considering state attributes of operators, and obtaining recommendation probability values of the situation information recommendation strategies; therefore, the situation information recommendation strategy with the highest recommendation probability value is selected as an information group for an operator to complete a task, the information group is intelligently displayed on an interaction interface, and the intelligence, interactivity and user satisfaction of a man-machine interaction system are improved.

Description

technical field [0001] The invention relates to the technical field of human-computer interaction, in particular to an FFM-based situational information classification and recommendation system and method under multi-task conditions. Background technique [0002] In recent years, research on multi-agent human-computer interaction has received great attention from academia and industry due to the wide application of human-computer interaction in military and civil fields. Human-computer interaction is the study of the relationship between the three elements of man, machine, and environment. In order to solve the problems of insufficient interactive performance, lack of intelligence, poor flexibility, and low user satisfaction in the system, it is necessary to research and develop a multi-agent information recommendation system. system. [0003] In the battlefield environment, when the operator is in the process of commanding and controlling the multi-agent system, under diff...

AI Technical Summary

Problems solved by technology

Human-computer interaction is the study of the relationship between the three elements of man, machine, and environment. In order to solve the problems of insufficient interactive performance, lack of intelligence, poor flexibility, and low user satisfaction in the system, it is necessary to research and develop a multi-agent information recommendation system. system

[0003] In the battlefield environment, when the operator is in the process of commanding and controlling the multi-agent system, under different complex tasks, different tasks have different requirements for different information, and the push of situational information will have a great impact on the operator's decision-making. At the same time, various attribute values ​​of the operator, such as proficiency, utilization and other factors will also affect the task results, but the existing recommendation systems and methods are all aimed at recommending the user's preference for the product in the Internet environment. Does not involve the battlefield environment, therefore, an information recommendation system and method suitable for complex and multi-task battlefields is needed

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