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| <h1 style='font-size:xx-large; color: green; text-align: center'>🍀 Green City Finder 🍀</h1> | |
| <h3 style="text-align: center">AI Sprint 2024 submissions by Ashmi Banerjee.<sup>*</sup></h3> | |
| <br> | |
| <p style="text-align: justify"> | |
| Tourism Recommender Systems (TRS) have traditionally focused on providing personalized travel suggestions, often | |
| prioritizing user preferences without considering broader sustainability goals. | |
| Integrating sustainability into TRS has become essential with the increasing need to balance environmental impact, | |
| local community interests, and visitor satisfaction. | |
| We enhance the traditional RAG system by incorporating a sustainability metric based on a city’s popularity and | |
| seasonal demand during the prompt augmentation phase. | |
| This modification, called <b>Sustainability Augmented Reranking (SAR)</b>, ensures the system's recommendations align with | |
| sustainability goals. | |
| </p> | |
| <p style="text-align: justify"><a href="https://arxiv.org/pdf/2403.18604">Sustainability score</a> for the retrieved | |
| destinations is calculated based on the following parameters: | |
| <ul> | |
| <li>Carbon footprint from the starting points to the retrieved cities using the greenest mode of travel (fly, drive, | |
| train) | |
| </li> | |
| <li>Overall popularity of the retrieved destinations based on their aggregated Tripadvisor reviews and opinions</li> | |
| <li>Seasonal footfall for the intended month of travel (if present)</li> | |
| </ul> | |
| </p> | |
| <p style="text-align: justify"> | |
| We test our implementation with Google's <b>Gemini</b> models | |
| through VertexAI to generate sustainable travel recommendations. | |
| We use the Wikivoyage dataset to provide city recommendations based on user queries. | |
| The vector embeddings are stored and accessed in a VectorDB (LanceDB) hosted in Google Cloud. | |
| </p> | |
| <p style="text-align: justify">This is an extension of the following work. To <b>cite</b>, please use the following:</p> | |
| <blockquote> | |
| <p> [1] <b>Enhancing sustainability in Tourism Recommender Systems,</b> <i>Ashmi Banerjee, Adithi Satish, Wolfgang | |
| Wörndl</i>, In Proceedings of the 1st International Workshop on Recommender Systems for Sustainability and Social | |
| Good (RecSoGood 2024), co-located with ACM RecSys 2024, Bari, Italy. | |
| </p> | |
| </blockquote> | |
| <blockquote> | |
| <p> [2] <b>Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems,</b> <i>Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, Wolfgang | |
| Wörndl</i>, arXiv preprint <a href="https://arxiv.org/abs/2403.18604">arXiv:2403.18604 (2024)</a>. | |
| </p> | |
| </blockquote> | |
| <br> | |
| <p style="text-align: justify; font-weight: bold"><sup>*</sup>Google Cloud credits are provided for this project.</p> | |
| <h2 style='font-size:large; color: black; text-align: left'>Instructions</h2> | |
| <ul> | |
| <li>Select the country and city where you're located.</li> | |
| <li>Enter the search query; it has to be something for which the system can recommend cities.</li> | |
| <li>Click the <b>Search</b> button to find the most sustainable recommendations for your <b>starting | |
| position</b>. | |
| </li> | |
| <li>Click the <b>Clear</b> button to clear the fields.</li> | |
| </ul> | |
| <p style="text-align: justify; color: darkred">Note that this works best if you ask it for <span | |
| style="font-weight: bold; color: darkred; text-underline: darkred">city</span> recommendations.</p> | |
| </body> | |