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Yandex Releases Yambda: The World’s Largest Event Dataset to Accelerate Recommender Systems
- Yandex has released Yambda, the world’s largest publicly available dataset for recommender system research, containing nearly 5 billion anonymized user interaction events from Yandex Music.
- This dataset aims to bridge the gap between academia and industry, offering valuable behavioral data for developing recommender systems.
- Recommender systems rely on massive behavioral data to provide personalized experiences, but access to such large, anonymized datasets has been limited.
- Yambda addresses this challenge by offering 4.79 billion anonymized user interactions over a 10-month period, with features like audio embeddings and organic interaction flags.
- The dataset is provided in Apache Parquet format, making it accessible for researchers and developers using big data processing frameworks.
- Yandex introduces a Global Temporal Split evaluation strategy in Yambda, preserving temporal order for realistic testing of recommender models.
- Baseline models like MostPop, DecayPop, ItemKNN, and others are included for benchmarking and assessing the performance of new algorithms.
- Yambda's applicability extends beyond music streaming, serving as a benchmark for recommender systems in various domains like e-commerce and social networks.
- My Wave, Yandex Music's personalized recommender system, utilizes deep neural networks to offer tailored music suggestions based on user preferences.
- Yandex emphasizes privacy in the dataset by anonymizing user data and omitting sensitive attributes, ensuring ethical use of the data for research purposes.
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