Knowledge Extraction from Large Scale Ontologies with Aibel
In this project, you will have a chance to explore how to extract relevant knowledge from large scale ontologies, ie Material Master Data (MMD) ontology, with Aibel .
Aibel is a large service company within the oil, gas and offshore wind industries. MMD ontology is developed for representing requirements and specifications that can help engineers select appropriate design artefacts and finding matching products. It is one of the biggest industrial ontologies. However, this ontology contains more than 1,800,000 axioms. It takes a lot of time to do reasoning on such large ontology. So the goal is that we can explore different techniques to extract relevant part of the ontology and reduce reasoning time.
The goal of this project is to find out a best strategy for extracting relevant knowledge from MMD ontology. W ith the help from the supervisor, you will
- read relevant papers about how to extract knowledge from ontology, such as ontology modularity;
- apply the knowledge that you learn from the course of "Semantic Technologies" in the real-world scenario;
- explore different knowledge extraction techniques and use reasoners on large scale ontologies;
- learn how to deal with industrial data and work with domain experts;
- build a framework of knowledge extraction for MMD ontology.
In this project, you have the chance to work with people both in the university and company and get more insight about how semantic technology are used in the large companies in Norway, such as Aibel. You are also free to work either on more practical applications in industry or investigate research questions that you are interested in and then apply them in real world scenario.
It would be very helpful if you are familiar with Java and interested in exploring semantic technologies.
Here you can find more information about Aibel and MMD ontology: slides .