Modeling Decisions for Artificial Intelligence

MDAI 2015: Modeling Decisions for Artificial Intelligence pp 167-179 | Cite as

Optimized and Parallel Query Processing in Similarity-Based Databases

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9321)


We present a novel method of query execution in similarity-based databases which adopts techniques commonly used in traditional programming language compilers. Our method is based on decomposition of relational algebra operators into a small set of simple operations which are subject of further optimizations. It shows up that with a small set of optimizations rules our system itself is able to infer efficient algorithms for data processing. Furthermore, operations we propose are compatible with the map/reduce approach to data processing, and thus, allows for implicitly parallel or distributed data processing.


Domain similarities Relational model of data Query execution Query optimization Fuzzy logic Parallel data processing 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Computer SciencePalacky UniversityOlomoucCzech Republic

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