Modern database management systems (DBMS) expose hundreds of configurable knobs to
control system behaviours. Determining the appropriate values for these knobs to improve …

Time series are generated in diverse domains such as economic, traffic, health, and energy,
where forecasting of future values has numerous important applications. Not surprisingly …

Hypergraphs can model higher-order relationships among data objects that are found in
applications such as social networks and bioinformatics. However, recent studies on …

Index advisors aim to improve workload performance by judiciously selecting an appropriate
set of indexes. Various heuristic-based and learning-based methods have been proposed …

Existing machine learning (ML) approaches to automatically optimize database
management systems (DBMSs) only target a single configuration space at a time (eg, knobs …

Many index advisors have recently been proposed to build indexes automatically to improve
query performance. However, they mainly consider performance improvement in static …

As large volumes of trajectory data accumulate, simplifying trajectories to reduce storage
and querying costs is increasingly studied. Existing proposals face three main problems …

Privacy-preserving record linkage (PPRL) is the process of linking records from various data
sources, ensuring that matching records for the same entity are shared among parties while …

Time series compression encodes the information in a time-ordered sequence of data points
into fewer bits, thereby reducing storage costs and possibly other costs. Compression …

Caching is a crucial solution to alleviate the high latency and low bandwidth of cloud
databases. However, existing caching algorithms are not suitable for cloud databases as 1) …