RecStore: an extensible and adaptive framework for online recommender queries inside the database engine

@inproceedings{Levandoski2012RecStoreAE,
  title={RecStore: an extensible and adaptive framework for online recommender queries inside the database engine},
  author={Justin J. Levandoski and Mohamed Sarwat and Mohamed F. Mokbel and Michael D. Ekstrand},
  booktitle={EDBT},
  year={2012}
}
Most recommendation methods (e.g., collaborative filtering) consist of (1) a computationally intense offline phase that computes a recommender model based on users' opinions of items, and (2) an online phase consisting of SQL-based queries that use the model (generated offline) to derive user preferences and provide recommendations for interesting items. Current application usage trends require a completely online recommender process, meaning the recommender model must update in real time as… CONTINUE READING

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Database System Support for Personalized Recommendation Applications

  • 2017 IEEE 33rd International Conference on Data Engineering (ICDE)
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RECATHON: A Middleware for Context-Aware Recommendation in Database Systems

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PLUTUS: Leveraging Location-Based Social Networks to Recommend Potential Customers to Venues

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Recommending Software Apps in a B2B Context

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RecDB: towards DBMS support for online recommender systems

  • SIGMOD/PODS PhD Symposium
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