This is a repository of public data sources for Recommender Systems (RS). All of these recommendation datasets can convert to the atomic files defined inRecBole, which is a unified, comprehensive and efficient recommendation library. After converting to the atomic files, you can use RecBole to te...
| Tenrec | Video, Article | General | Tenrec is a large-scale benchmark dataset for recommendation systems. It contains around 5 million users and 140 million interactions. | [link](https://tenrec0.github.io/) |This link contains all the datsets regarding RecSys - [link](https://csewe...
Healthcare Recommendation Systems (HRSs) primarily aim to offer advice, recommendations, or suggestions related to human healthcare. Similar to other information systems, datasets affect HRSs' efficiency. The larger datasets can make the information more diverse and complete. Therefore, the recommendation...
Therefore, the recommendation systems can be more accurate and deliver better performance. In addition, several recent studies have revealed that to enhance the accuracy of systems, there should be a switch from a model-centered method to data-centricity. Therefore, several datasets have been ...
Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on
The mission of MIND is to serve as a benchmark dataset for news recommendation and facilitate the research in news recommendation and recommender systems area.MIND contains about 160k English news articles and more than 15 million impression logs generated by 1 million users. Every news article ...
斯坦福大学关于海量数据的挖掘的免费教材《MiningofMassiveDatasets》Mining of Massive Datasets Anand Rajaraman Kosmix,Inc.Jeffrey D.Ullman Stanford Univ.Copyright c 2010,2011Anand Rajaraman and Jeffrey D.Ullman
Microsoft News recommendation dataset Microsoft News Dataset (MIND) is a large-scale dataset for news recommendation research. It serves as a benchmark dataset for news recommendation, and facilitates research in news recommendation and recommender systems. Public holidays Worldwide public holiday data so...
An analysis of sequential recommendation datasets. PERSPECTIVES, 2021.Harper F. M. and Konstan J. A. The MovieLens datasets: History and context. ACM Transactions on Interactive Intelligent Systems.概本文讨论了 MovieLens 系列数据集是否适用于序列推荐....
Companies may have access to large, proprietary datasets that are not publicly available, such as customer data, transaction data, or user behaviour data. These datasets can be used to train AI models for specific applications, like recommendation systems or fraud detection. ...