Angjela Davitkova(AG Database and Information Systems, Prof. Michel)
hosted by PhD Program in CS @ TU KL
"Optimizing Data Management using Machine Learning Approaches"
Recently, the usage of machine learning has majorly expanded, highly impacting the research field of the improvement or replacement of database concepts. Firstly focusing on the enhancement of traditional database indexes, this thesis proposes the ML-Index, a memory-efficient Multidimensional Learned (ML) structure for processing point, KNN, and range queries. Using data-dependent reference points, the ML-Index partitions the data and transforms it into one-dimensional values relative to the distance to their closest reference point. Once scaled, the ML-Index utilizes a learned model to efficiently approximate the order of the scaled values in combination with a novel offset scaling method. The future scope of the thesis will include a further extension of the ML-Index, as well as expansion of the research area towards different data formats and learning enhanced optimization of query processing. Through a thorough experimental performance comparison and a discussion regarding the future research area, the feasibility and the supremacy of the ML-Index, as well as a promising direction of this thesis are shown.
|Time:||Monday, 29.06.2020, 15:30|