Traditional methods are difficult to classify animals scientifically and effectively based on their multiple attributes. In this paper, we establish a multi-level knowledge graph expert system to classify animals scientifically and effectively. Specifically, we implement a hierarchical knowledge graph of direct and indirect rules to enable the scientific and effective matching of multiple attributes to animal categories. Our software implements a knowledge graph expert system and achieves significant results. Our approach can be used as a reference for intelligent attribute classification of goods and objects.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Animal Attribute Classification via Knowledge Graph Expert System


    Contributors:


    Publication date :

    2021-10-20


    Size :

    1274579 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Graph attribute embedding via Riemannian submersion learning

    Zhao, H. / Robles-Kelly, A. / Zhou, J. et al. | British Library Online Contents | 2011


    A Min-Max Graph Application to the Base of Knowledge Organization of the Expert System

    Nawarecki, E. / Cetnarowicz, K. / Marcjan, R. et al. | British Library Online Contents | 1993


    Expert knowledge based SPC quality system

    Ngo,B. / Fern,A.G. / Krabbe,P.M. et al. | Automotive engineering | 1998


    Integration of Expert System Knowledge Bases

    Laikov, T. V. / Khirug, S. S. | British Library Online Contents | 1996


    Knowledge-Acquisition Tool For Expert System

    Disbrow, James D. / Duke, Eugene L. / Regenie, Victoria A. | NTRS | 1988