Fully Automated Ontology Increment`S user Guide Generation

This research focuses on a domain and schema independent user-guide generation for ontology increments. Having a user guide or a catalogue/manual is vital for quick and effective knowledge dissemination. If a user guide can be generated for an ontology as well, there could be ample advantages. Stakeholders can scan across the user guide of the ontology and verify the eligibility of it, against the intended purposes. Additionally, this could be useful in ontology`s version management requisites and knowledge verification requirements as well. Even though, ontology construction being iterative and incremental operational, there will be several intermediate versions before it reaches to the fine-tuned final version. Therefore, manual user guide creation will be a tedious and impossible operation. Consequently, this research focuses on a novel algorithmic approach to domain and schema independent ontology verbalization. A special algorithm is created to alter the functionality of Google`s AliceBot to work as a verbalizer, instead of a chatterbot. Artificial Intelligent Modelling Language (AIML) technology is utilized to create the templates for the ontology specific knowledge embeddings. This entire process is fully automated via the proposed novel algorithm, which is a key contribution of this research. Eventually, the generated user guide generation tool is evaluated against three different domains with the involvement of fifteen stakeholders and 82% of averaged acceptance has been yielded.

@article{Vidanage2021,
  title     = {Fully Automated Ontology Increment`S user Guide Generation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Kaneeka Vidanage and Rosmayati Mohemad and Noor Maizura Mohamad Noor and Zuriana Abu Bakar},
  doi       = {10.14569/IJACSA.2021.0120624},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120624}
}