A Holistic Approach for Automatic Deep Understanding and Protection of Technical Documents
Nikolaos Bourbakis, Sukarno J. Mertoguno · International Journal of Artificial Intelligence Tools · 2020
A Technical Document (TD) is mainly composed by a set of modalities appropriately structured and associated. These modalities could be NL-text, block diagrams, formulas, tables, graphics, pictures etc. A deep understanding of a TD will be based on the synergistic understanding and associations of these modalities. This paper offers a novel methodology for the implementation of a holistic approach for deep understanding of technical documents by understanding and associating these modalities. This approach is based on the homogeneous expression (mapping) of the technical document modalities into the same medium, which in this case is the Stochastic Petri-nets (SPN). Then, these modalities are associated to each other generating new knowledge about the technical document topic and a SPN simulator is created to offer additional information about the functional behavior of the system described in the document. Some results from our studies are provided to prove the overall concept.