A Situation Intelligence Cognition Method Based on Active Semantic Text Messages

Abstract

The invention provides a situational intelligence cognition method based on active semantic text messages, which belongs to the field of confrontational semantic situational cognition. By analyzing the behavioral state semantic message data describing the situational elements, extracting the deep situational semantics contained in it and realizing the deep fusion of confrontational situational information at the semantic layer. On the basis of combining relevant knowledge, construct the semantic expression mode of typical behavior activities of typical targets in the confrontation, and on this basis, carry out semantic reasoning on the evolution trend of the confrontation situation, build an intelligent cognitive model of the global confrontation situation, and use the constructed situation The cognitive model outputs situational cognitive semantic results such as intent recognition and threat assessment, assisting command and decision-makers to quickly, deeply and comprehensively understand the overall situation.

Description

technical field [0001] The invention belongs to the field of semantic situational cognition, in particular to an intelligent situational cognition method based on active semantic text messages. Background technique [0002] Confrontation situational awareness is the process of recognizing, understanding and predicting situational elements, and it is the key technology for both sides to gain information advantages. It is a research hotspot in many fields such as information fusion and target surveillance. The cognition of the confrontation situation is mainly reflected in two aspects: situational information fusion and confrontation situation cognition. [0003] In terms of situational data fusion, at this stage, adaptive estimation, ontology theory, fuzzy theory, etc. are often used to reason, qualitative and quantitative fusion of situational data, and some results have been achieved. However, the current common situational fusion methods generally lack the ability to und...

AI Technical Summary

Problems solved by technology

[0004] In terms of confrontation situation cognition, fuzzy theory, Petri network, Bayesian network, entropy weight gray correlation method, and D-S evidence method are often used at this stage. These methods are practical and effective for situation cognition to a certain extent. However, these methods are generally difficult to effectively understand the dynamics and uncertainties of the confrontation situation.

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