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Information retrieval techniques have been traditionally exploited outside of relational database systems, due to storage overhead, the complexity of programming them inside the database system, and their slow performance in SQL implementations. This paper supports the idea that searching and querying digital libraries with information retrieval models in relational database systems can be performed with optimized SQL queries and User-Defined Functions. In the authors' research, they propose several techniques divided into two phases: storing and retrieving. The storing phase includes executing document pre-processing, stop-word removal and term extraction, and the retrieval phase is implemented with three fundamental IR models: the popular vector space model, the okapi probabilistic model, and the dirichlet prior language model.
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