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1. Finding the Experts
Having settled with the project theme and design, it was time to start looking for experts that could help gather the necessary knowledge to develop the expert system for customer satisfaction diagnosis.
The team settled on a profile that the experts should have: a solid background in data analytics and customer relations. Afterwards, each team member started looking for experts within their companies, having found the two experts presented bellow:
Diogo Cardoso
With 5+ years of experience in data analytics, at companies such as Deloitte and Farfetch, Diogo will be able to help us determine the best client metrics and the rules that will allow the expert system to determine a client's degree of satisfaction.
Tiago Ribeiro
Having worked for 10+ years at companies such as Sony and SONAE, Tiago has a very solid background in customer relations and data analytics, which will be very helpful when suggesting plans of action to build back the trust from unsatisfied clients.
The team believes that having two perspectives on the same problem will prove very helpful and beneficial for the expert system development, as it should result in a richer knowledge base and, therefore, a stronger performance from the expert system.
2. Blog Creation
As per requested by the professors, the team created this blog, where weekly updated will be provided, reporting the current state of the project's development and any major decisions that was made by the team.
Stay tuned for more updates in the following weeks!
3. Project Planning
With only 5 weeks left in the project's development, the team decided to plan a project roadmap, where the following goals/expected results for each week were settled, although it may be prone to changes in the future:
Week #3
Obtain the required knowledge to implement an initial version of the expert system, resorting to Drools;
Finish the development of the Data Management Module.
Week #4
Demonstrate the current version of the expert system to the experts and refine/expand the currently obtained knowledge based on the experts' feedback;
Finish writing the first version of the report requested by Knowledge Engineering course unit.
Week #5
Having refined the obtained knowledge in the previous week, implement the changes in the Drools expert system;
Implement the improvements in the inference mechanism implemented in Prolog, allowing the second version of expert system to be implemented resorting to it;
Week #6
Finish the implementation of the expert system in Prolog;
Finish the development of the Single Page Application.
Connect the different modules composing the web application, resulting in a fully functional system;
Demonstrate the web application and the expert systems integrated in it to the experts, in order to obtain more feedback to further improve the entire system.
Week #7
Finish writing the final version of the report requested by Knowledge Engineering course unit;
Finish writing the article requested by Artificial Intelligence Programming Paradigms course unit;
Finish the implementation of the final version of the Customer Satisfaction Diagnosis system, including the web application and the expert systems integrated in it.
In the following weeks' posts, the team will check if everything is on track, by confronting the obtained results with the ones defined in the project roadmap.
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