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This project is to build a smart traveler assistant (STA) software system for Free Independent Travelers (FIT). FIT is a travel style where a person plans and books all aspects of their trip themselves, including transportation, accommodations, and itinerary. This STA could plan and book the itinerary before traveling and could replan and rebook the travel activities during traveling according to the real situations. In Dr. Yuhong Yan and her students’ previous research, an automatic travel planner was built based on automatic service composition. All the traveling activities are modelled as services and a service is abstracted as a common model whose properties include cost, time, location, etc. Thus, service composition algorithm is developed to integrate the services into a plan using planning techniques. Although the planning algorithm developed can solve the problem well, the main difficulty is to understand user requirements described in natural language. The current advances in Large Language Model (LLM) can solve the problem of user requirements understanding. We plan to use Retrieval Augmented Generation (RAG) to control how LLM responses to user input. More specifically, the common properties of services are going to be modelled and the values of the properties are going to be extracted using RAG + LLM. Then, we could properly model user requirements and then extend our existing travel planner to build a true STA. Our industrial partner is Concord Tour & Travel. This is a Montreal based travel agency. It has full-fledged product lines from airplane tickets, bus tour, to group travel groups to many destinations. Concord senses the trend changes in tourism industry and is interested to build a smart FIT assistant. Their domain expertise will play a crucial role in ensuring the success of the final product.
Yuhong Yan
Concord Tour and Travel
Computer science
Transportation and warehousing
Concordia University
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