Kristin Fritsch

dblp:273/4479 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none

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

Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data integration and cleaning · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Emerging computing paradigms · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Data integration and cleaning
schema matching
0.712023
Solving Hard Variants of Database Schema Matching on Quantum Computers · Proc. VLDB Endow. 2023
Emerging computing paradigms › quantum computer architecture
hybrid quantum-classical computing
0.212023
Solving Hard Variants of Database Schema Matching on Quantum Computers · Proc. VLDB Endow. 2023
Emerging computing paradigms
quantum computer architecture
0.212023
Solving Hard Variants of Database Schema Matching on Quantum Computers · Proc. VLDB Endow. 2023

Methods — techniques the papers use, named apart from their topics

hybrid quantum algorithms · 1.3QPU-CPU cooperation · 1.3
YearPublicationVenuePosition
2023 Solving Hard Variants of Database Schema Matching on Quantum Computers
abstract
With quantum computers now available as cloud services, there is a global quest for applications where a quantum advantage can be shown. Naturally, data management is a candidate domain. Workable solutions require the design of hybrid quantum algorithms, where a quantum computing unit (a QPU) and classical computing (via CPUs) cooperate towards solving a problem. This demo illustrates such an end-to-end solution targeting NP-hard variants of database schema matching. Our demo is intended to be educational (and hopefully inspiring), allowing participants to explore the critical design decisions, such as the handover between phases of QPU- and CPU-based computation. It will also allow participants to experience hands-on - through playful interaction - how easily problem sizes exceed the limitations of today's QPUs.
Kristin Fritsch, Stefanie Scherzinger
Proc. VLDB Endow.1