English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper discusses the design and implementation of a knowledge based Modelling system KMS, which combines semantic and rule based approaches in the modelling process. The design and implementation of the semantic concepts are controlled dynamically to achieve an optimal degree of reality and to employ efficient interactivity and accessibility for the user. The model-based controlling module is developed to achieve efficiency and consistence in the basic analysis process, and to avoid the static structure that frequently occurs in data driven systems. By using a hypothesis and verification scheme in order to ensure interactivity and accessibility without sacrificing efficiency the KMS evokes the important task of merging the use of heuristic knowledge in form of a knowledge base with domain specific requirements. By detecting contradicting and inconsistent rules and by performing tests in the knowledge base and finally by creating new hypothesis to solve the problems, the controlling process also provides the decision module with a concept for automated knowledge refinement. This paper focuses on the implementation and Multimedia adaptation of the learning processes in correlation with the linked databases.

KNOWLEDGE BASED 3D-MODELLING BY SELFORGANISED LEARNING ALGORITHMS - Image understanding based on automated knowledge refinement