FRINK Linked Data Fragments server

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• W2186138942 abstract "We describe FactorBase, a new SQL-based framework that leverages a relational database management system to support multi-relational model discovery. A multi-relational statistical model provides an integrated analysis of the heterogeneous and interdependent data resources in the database. We adopt the BayesStore design philosophy: statistical models are stored and managed as first-class citizens inside a database [30]. Whereas previous systems like BayesStore support multi-relational inference, FactorBase supports multi-relational learning. A case study on six benchmark databases evaluates how our system supports a challenging machine learning application, namely learning a first-order Bayesian network model for an entire database. Model learning in this setting has to examine a large number of potential statistical associations across data tables. Our implementation shows how the SQL constructs in Factor-Base facilitate the fast, modular, and reliable development of highly scalable model learning systems." @default.
• W2186138942 created "2016-06-24" @default.
• W2186138942 creator A5026297632 @default.
• W2186138942 creator A5027172369 @default.
• W2186138942 date "2015-10-01" @default.
• W2186138942 modified "2023-09-27" @default.
• W2186138942 title "FactorBase : Multi-relational model learning with SQL all the way" @default.
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• W2186138942 doi "https://doi.org/10.1109/dsaa.2015.7344828" @default.
• W2186138942 hasPublicationYear "2015" @default.
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