Resemblance relations for cognitive systems

Teachers: 
Edy Portmann
Sara D’Onofrio
ICT Post
Project status: 
Open
Year: 
2018

To build a cognitive system, it is crucial to develop a memory in the form of a knowledge base from which the system is able to retrieve information as a human being would. A potential approach is to use resemblance relations. With the help of this technique, the system will be able to find similar information, even if at first sight the connection is not immediately obvious. Based on fuzzy logic, it is possible to build knowledge maps (e.g., fuzzy cognitive maps or neural networks) in which nodes would be connected through edges/connectors. Nodes consist of concepts or objects, and edges/connectors illustrate the relationship between nodes. Due to the network-like memory the system will be able to understand what information is similar, and so, by using resemblance relations, the system should be able to match the question with the best possible answer.

Therefore, this master thesis should achieve the following goals:

  • Conceptual/mathematical description of resemblance relations (e.g., documentation)
  • Elaboration of possible ways to implement resemblance relations within an existing knowledge base (e.g., building a framework/prototype)
  • Testing and evaluating the use of resemblance relations in a knowledge base of a real project

This master thesis helps to find out if resemblance relations could be applied to optimizing the matching of questions and answers in an existing knowledge database. During the project, the participant will also have the opportunity to gain an insight into projects running at IcT Post and to benefit from the units approach and competences.