This section discusses the prepared product listing features and proposition for their implementation and further refinement.
The AI engine is our solution encompassing the analytical capabilities based on the newly desiged ontology. It is a foundation enabling navigating the ontology, efficient search, browsing of OER, as well as makes smoother user journey through the portal and creates opportunities for employing the AI-based functionalities.
- The knowledge base that is created, codifies information and then an ontology is developed that reflects associations among different data elements. Ontology-based AI allows the system to make inferences based on content and relationships, and therefore emulates human performance.
- AI Engine is comprised of several fundamental modules which include
- a Machine Learning Module
- a Natural Language Processing Module
- a Knowledge Representation(Ontology) Module
- a UI Interface (OpenEdu.ch Platform)
- The core of an AI Engine is implemented as an ontology which may be populated by default with a huge amount of general knowledge (e.g. the whole of Wikipedia in the form of DBPedia)
The code examples rely on a wide range of Python libraries from the Data Science and NLP domains. To facilitate installation, I use Docker to provide containerized conda environments.
- The installation directory contains detailed instructions on setting up and using a Docker image to run the notebooks. It also contains configuration files for setting up various
condaenvironments and install the packages used in the notebooks directly on your machine.
