The BITeS Food Outlet Recommender is an expert system-based application built using the experta library in Python. It provides personalized recommendations for food outlets based on user preferences and requirements. By answering a series of questions, the system uses logical reasoning to suggest suitable food outlets that match the user's criteria.
This project demonstrates the implementation of an expert system using the experta library, which offers a rule-based inference engine for creating knowledge-based applications. It showcases how expert systems can be used to provide intelligent recommendations in specific domains.
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Rule-based inference engine for generating personalized recommendations from outlets from our campus
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Knowledge base with consists of food outlets from BITS hyderabad
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The inference engine uses various parameters to come up with the best possible recommendations using a score based approach
- The expert system is also able to generate more than one responses if it finds more than one outlets which satisfy users query
- Other examples
- Python 3.x
- Install the required dependencies by running the following command:
pip install experta