Bachelor and Master Theses

Title: USING DOMAIN KNOWLEDGE FUNCTIONS TO ACCOUNT FOR HETEROGENEOUS CONTEXT FOR TASKS IN DECISION SUPPORT SYSTEM FOR PLANNING
Subject: Computer Science
Level: Basic
Description: This thesis describes a way to represent domain knowledge as functions. Those functions can be composed and used for better predicting time needed for a task. These functions can aggregate data from different systems to provide a more complete view of the contextual environment without the need to consolidate data into one system. These functions can be crafted to make problem and domain specific diagnostics and prognostics, e.g. a more precise time prediction for a specific task that needs to be carried out in a specific context. We describe a possible way to structure and model data that could be used with the functions.

As a proof of concept a prototype was developed to test a fictional scenario with simu- lated data. The prototype is compared to predictions using min, max and average values from previous experience. The result shows that domain knowledge, represented as functions can be used for improved prediction.

This way of defining functions for domain knowledge can be used as a part of a CBR system to provide decision support in a problem domain where information about context is avail- able. It is scalable in the sense that more context can be added to new tasks over time and more functions can be added and composed. The functions can be validated on old cases to assure consistency.
Company: SAAB GROUP, kontaktperson: Ella Olsson
Student: Anton Roslund ard15003@student.mdh.se
IDT supervisors:
Peter Funk
peter.funk@mdh.se, +46-21-103153
     
Examinator: Ning Xiong
Ning Xiong
ning.xiong@mdh.se, +46-21-151716

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