Christina Khnaisser

dblp:168/2205 · DBLP profile ↗
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4ranked-venue papers
2as first author
3since 2021 · last 2025
0000-0002-1186-0300ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 4 · 2 first-author · 3 since 2021Artificial intelligence and machine learning · 1 · 1 first-author
YearPublicationVenuePosition
2025 Indexing temporal relations for range-duration queries
abstract
Abstract Temporal information plays a crucial role in many database applications, however support for queries on such data is limited. We present an index structure, termed RD-index , to support range-duration queries over interval timestamped relations, which constrain both the range of the tuples’ positions on the timeline and their duration . RD-index is a grid structure in the two-dimensional space, representing the position on the timeline and the duration of timestamps, respectively. Instead of using a regular grid, we consider the data distribution for the construction of the grid in order to ensure that each grid cell contains approximately the same number of intervals. RD-index features provable bounds on the running time of all the operations, allows for a simple implementation, supports very predictable query performance, and can be constructed and queried in parallel using multithreading. We benchmark our solution on a variety of datasets and query workloads, investigating both the query rate and the behavior of the individual queries. The results show that RD-index performs better than the baselines on range-duration queries, for which it is explicitly designed. Furthermore, it outperforms state of the art indexes also on mixed workloads containing queries that constrain either only the duration or the range along with range-duration queries. Finally, the size of the RD-index is in all settings smaller than the competitors, its construction scales with the number of threads, and parallelization helps improving the runtime of expensive moderate and lowly selective queries.
Matteo Ceccarello, Anton Dignös, Johann Gamper, Christina Khnaisser
Distributed Parallel Databases4
2023 Indexing Temporal Relations for Range-Duration Queries
abstract
Temporal information plays a crucial role in many database applications, however support for queries on such data is limited. We present an index structure, termed RD-index, to support range-duration queries over interval timestamped relations, which constrain both the range of the tuples’ positions on the timeline and their duration. RD-index is a grid structure in the two-dimensional space, representing the position on the timeline and the duration of timestamps, respectively. Instead of using a regular grid, we consider the data distribution for the construction of the grid in order to ensure that each grid cell contains approximately the same number of intervals. RD-index features provable bounds on the running time of all the operations, allow for a simple implementation, and supports very predictable query performance. We benchmark our solution on a variety of datasets and query workloads, investigating both the query rate and the behavior of the individual queries. The results show that RD-index performs better than the baselines on range-duration queries, for which it is explicitly designed. Furthermore, it outperforms state of the art indexes also on mixed workloads containing queries that constrain either only the duration or the range along with range-duration queries. Finally, the size of the RD-index is in all settings smaller than the competitors.
Matteo Ceccarello, Anton Dignös, Johann Gamper, Christina Khnaisser
SSDBM4
2022 Querying Temporal Anomalies in Healthcare Information Systems and Beyond
Christina Khnaisser, Hind Hamrouni, David B. Blumenthal, Anton Dignös, Johann Gamper
ADBIS1
2017 Past Indeterminacy in Data Warehouse Design
Christina Khnaisser, Luc Lavoie, Anita Burgun-Parenthoine, Jean-François Ethier
DEXA (2)1