Personalized Event Recommender System Development

The main goal of this project is to develop a personalized events recommender system that suggests events to users based on their preferences and behaviors, using aggregated event data. This involves building a recommendation algorithm, integrating it with an event aggregator platform, and designing an engaging user interface to display the recommendations, ultimately enhancing user engagement with the platform.

App Chat to IRL: A GenZ Dating Capstone

The project aims to investigate whether auto-generated prompts suggesting real-life (IRL) meetups, timed strategically during a dating app match journey and based on shared interests, can improve relationship success among GenZ users. Many GenZ users face anxiety when transitioning from digital conversations to in-person meetings. By introducing specific, tailored prompts based on mutual interests, the project seeks to make this transition smoother and encourage IRL interactions. The hypothesis is that providing timely, context-specific prompts for in-person meetups based on user interests will enhance relationship outcomes and reduce anxiety. The project will involve developing and testing these prompts, aggregating potential date options, and measuring their effectiveness through pilot studies and user feedback. Key Points: - Investigate the impact of auto-generated IRL meetup prompts on relationship success. - Address anxiety faced by GenZ users in transitioning from online to offline interactions. - Develop and test prompts based on mutual interests and user profiles. - Measure effectiveness through pilot studies and user feedback.

Automating Event Listings with Generative AI

The main goal for the project is to use generative AI, such as ChatGPT, to take an Event URL as an input parameter, structure the event information, label the data, and generate a listing for the event that can be used and shared within an event discovery platform. This exploratory prototyping project will involve several different steps for the learners, including: Understanding the structure and content of event URLs. Learning how to use generative AI, such as ChatGPT, to process and label event data. Developing a system to generate a structured event listing from the processed data. Testing the generated event listing for accuracy and usability within an event discovery platform. Developing a method to re-check the URL for information updates.