Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

A Comprehensive Survey of Cognitive Graphs: Techniques, Applications, Challenges

Version 1 : Received: 5 August 2021 / Approved: 6 August 2021 / Online: 6 August 2021 (10:14:00 CEST)

How to cite: Chen, M.; Tian, Y.; Wang, Z.; Xu, H.; Jiang, B. A Comprehensive Survey of Cognitive Graphs: Techniques, Applications, Challenges. Preprints 2021, 2021080155 (doi: 10.20944/preprints202108.0155.v1). Chen, M.; Tian, Y.; Wang, Z.; Xu, H.; Jiang, B. A Comprehensive Survey of Cognitive Graphs: Techniques, Applications, Challenges. Preprints 2021, 2021080155 (doi: 10.20944/preprints202108.0155.v1).

Abstract

The realization of the third-generation artificial intelligence (AI) requires the evolution from perceptual intelligence to cognitive intelligence, where knowledge graphs may not meet the practical needs anymore. Based on the dual channel theory, cognitive graphs are established and developed through coordinating the implicit extraction module and the explicit reasoning module as well as integrating knowledge graphs, cognitive reasoning and logical expressions, which have achieved successes in multi-hop question answering. It is desired for cognitive graphs to be widely used in advanced AI applications such as large-scale knowledge representations and intelligent responses, promoting the development of Al dramatically. This review discusses cognitive graphs systematically and elaborately, including basic concepts, generations, theories and technologies. Moreover, we try to predict the development of cognitive intelligence in the short-term future and further enlighten more researches and studies.

Keywords

Cognitive Graph; Knowledge Graph; Knowledge Reasoning; Natural Language Generating

Subject

MATHEMATICS & COMPUTER SCIENCE, Artificial Intelligence & Robotics

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