View source for Building a Knowledge-based AI Framework for Mobility

{{StudentProjectTemplate
|Summary=Leveraging new knowledge to improve the productivity of mobility services
|Keywords=Knowledge-base, AI, Recommendation, Mobility
|TimeFrame=Fall 2021
|Prerequisites=Knowledge of AI, knowledge-based systems, and machine learning
|Supervisor=Enayat Rajabi, Sławomir Nowaczyk
|Level=Master
|Status=Open
}}
Knowledge acquisition is the process of extracting and structuring data or information from various sources, including human experts, and storing the information into a knowledge-base. It can be seen as a process of adding new knowledge to a knowledge-base and refining or improving the knowledge that was previously acquired. This process may consist of facts, rules, concepts, procedures, heuristics formulas, relationships, statistics any other useful information. Knowledge acquisition can be performed by leveraging artificial intelligence to automatically discover knowledge from various datasets. The objective of this thesis is to build a knowledge-based framework for mobility using artificial intelligence with the intent of increasing the quality of knowledge, productivity of mobility services and providing personalized mobility services to travellers.