RecStore: An Extensible and Adaptive Framework for Online Recommender Queries inside the Database Engine

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Provided by: Microsoft Research
Topic: Data Management
Format: PDF
Most recommendation methods (e.g., collaborative filtering) consist of a computationally intense offline phase that computes a recommender model based on users' opinions of items, and 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 new opinions enter the system. To tackle this problem, the authors propose RecStore, a DBMS storage engine module capable of efficient online model maintenance.
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