2026
Currently developing iOS applications using Swift and SwiftUI
CBR Independent Study – Fall 2023 · Advised by Larry Gates & David Leake
A Case-Based Reasoning (CBR) project exploring AI-driven recommendations based on historical data. Over thirteen weeks, this journey revealed the dynamic nature of AI and its adaptability through real-world applications.
Explored case-based reasoning as a method for generating recommendations based on historical data. Contrary to initial assumptions, CBR proved to be versatile and adaptable to various scenarios, as exemplified by real-world applications like Google Maps and customer service chatbots.
The Customer Support CBR system focuses on troubleshooting steps generated from a help-desk dataset. With a flexible design, it accommodates diverse inputs, identifying and presenting top matching records based on attributes like ‘DeviceType,’ ‘OperatingSystem,’ ‘DeviceAge,’ ‘ModelNumber,’ and ‘IssueDetails.’ The weighting process and similarity metric ensure nuanced and accurate recommendations.
Developing the Travel Agent CBR posed challenges, from parsing data to handling user input and calculating similarities. The system evaluates attributes such as recreation, number of persons, region, transportation, duration, season, and accommodation, applying customized weights and distance metrics. An adaptation feature empowers users to tailor their travel packages.
The Travel Agent CBR project highlighted the flexibility and effectiveness of case-based reasoning. The journey revealed its adaptability and specific solutions derived from past experiences. Examples like Google Maps and customer support chatbots showcase its versatility, surpassing initial expectations.
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