University Honors

Homelessness continues to be a major social issue in the United States, and one practical challenge is that people who need help often have difficulty finding clear and reliable information about available services. Food assistance, shelter programs, mental health support, and other community resources are often listed across different online directories, but these directories can be difficult to search quickly. This capstone project developed a retrieval-based artificial intelligence system for organizing and searching homeless-support and community resource information. The system was built in Python using structured service data stored in CSV format. Service records were represented as subjectñrelationshipñobject triples, allowing each providerís name, service category, address, phone number, website, ZIP code, and hours of operation to be stored in a consistent format. The system used sentence-transformer embeddings and FAISS similarity search to match user questions with relevant service records. It also used ZIP code and city-based location cues to prioritize services relevant to the userís requested area. Testing showed that the system could return multiple structured service recommendations for queries involving food assistance, location-based searches, and day-of-week availability. Instead of giving a single answer, the system presented several matching services with practical details such as address, phone number, website, and operating hours. Although the system depends on the accuracy and completeness of the underlying dataset, the project demonstrates how retrieval-based AI methods can make community resource information more organized, searchable, and accessible.