The Solar Power Generation Data dataset provides synchronized inverter-level AC/DC power and yield measurements together with plant-level weather sensor observations from two grid-connected photovoltaic plants in India over 34 days at approximately 15‑minute resolution.
It comprises four CSV files including one generation file and one sensor file for each plant which totals about 2 MB, enabling compact yet information-dense time-series analysis.
We released one LLM generated recommendation dataset and one real-world employment dataset. The LLM generated dataset contains experiments over 9 social groups, 4 college degrees, 17 degree fields, 12 universities, 2 target work locations, and 383 occupation categories, resulting in 14,688 scenarios in total. The real employment dataset is retrieved from LinkedIn via API. The retrieved dataset contains approximately 295,000 individuals and a total of 1,330,000 records.
The Travel Recommendation Dataset is a comprehensive dataset designed for building and evaluating conversational recommendation systems in the travel domain. It includes detailed information about users, destinations, and ratings, enabling researchers and developers to create personalized travel recommendation models. The dataset supports use cases such as personalizing travel recommendations, analyzing user behavior, and training machine learning models for recommendation tasks.
All the healthcare facilites in this dataset were collected from the MOH 2018 list of Uganda healthcare facilites (https://library.health.go.ug/sites/default/files/resources/National%20Health%20Facility%20MasterLlist%202017.pdf) Additional features were scraped using the Google Maps API and additionally from some of the websites of the healthcare facilities themselves.
This dataset contains survey results collected from new recommendation system. This dataset asks about how the people accept recommendation systems from the AI trustworthiness and recommendation quality aspect.
