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

A recommendation method and information recommendation technology, applied in the field of human-computer interaction, can solve the problems of low user satisfaction, influence, lack of intelligence, etc.

Active Publication Date: 2021-05-18
BEIJING INSTITUTE OF TECHNOLOGYGY
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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 dif

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

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Embodiment Construction

[0048] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0049] Aiming at the problems of insufficient interactive performance, lack of intelligence, poor flexibility, and low user satisfaction in the human-computer interaction system, the present invention provides an FFM-based situational information classification and recommendation system and method under multi-task conditions, and establishes Based on Pew's task processing model, analyze the current task status information, according to the different attention of different tasks to different situation information, and consider the operator's status attributes, use the FFM model to calculate the task completion probability under different situation information recommendation strategies, and get The recommended probability value of the situational information recommendation strategy; thus, the situational information recommendation strategy with the highest re...

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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...

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Application Information

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IPC IPC(8): G06F3/01G06F16/9535G06F17/18
CPCG06F3/011G06F16/9535G06F17/18Y02D10/00
Inventor 方浩李嘉诚杨庆凯曾宪琳商成思宋晨班超李尚昊陈杰
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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