http://dl.gi.de/handle/20.500.12116/40312 2026-07-21T13:39:22Z 2026-07-21T13:39:22Z Schüle, Maximilian Emanuel Kemper, Alfons Neumann, Thomas http://dl.gi.de/handle/20.500.12116/40392 2023-02-23T14:00:26Z 2023-01-01T00:00:00Z

NN2SQL: Let SQL Think for Neural Networks Schüle, Maximilian Emanuel; Kemper, Alfons; Neumann, Thomas König-Ries, Birgitta; Scherzinger, Stefanie; Lehner, Wolfgang; Vossen, Gottfried Although database systems perform well in data access and manipulation, their relational model hinders data scientists from formulating machine learning algorithms in SQL. Nevertheless, we argue that modern database systems perform well for machine learning algorithms expressed in relational algebra. To overcome the barrier of the relational model, this paper shows how to transform data into a relational representation for training neural networks in SQL: We first describe building blocks for data transformation in SQL. Then, we compare an implementation for model training using array data types to the one using a relational representation in SQL-92 only. The evaluation proves the suitability of modern database systems for matrix algebra, although specialised array data types perform better than matrices in relational representation.

2023-01-01T00:00:00Z Köhnen, Christoph http://dl.gi.de/handle/20.500.12116/40391 2023-03-06T17:58:32Z 2023-01-01T00:00:00Z

BTW 2023 - Complete proceedings Köhnen, Christoph König-Ries, Birgitta; Scherzinger, Stefanie; Lehner, Wolfgang; Vossen, Gottfried

2023-01-01T00:00:00Z Hättasch, Benjamin Bodensohn, Jan-Micha Vogel, Liane Urban, Matthias Binnig, Carsten http://dl.gi.de/handle/20.500.12116/40390 2023-02-23T14:00:24Z 2023-01-01T00:00:00Z

WannaDB: Ad-hoc SQL Queries over Text Collections Hättasch, Benjamin; Bodensohn, Jan-Micha; Vogel, Liane; Urban, Matthias; Binnig, Carsten König-Ries, Birgitta; Scherzinger, Stefanie; Lehner, Wolfgang; Vossen, Gottfried n this paper, we propose a new system called WannaDB that allows users to interactively perform structured explorations of text collections in an ad-hoc manner. Extracting structured data from text is a classical problem where a plenitude of approaches and even industry-scale systems already exists. However, these approaches lack in the ability to support the ad-hoc exploration of texts using structured queries. The main idea of WannaDB is to include user interaction to support ad-hoc SQL queries over text collections using a new two-phased approach. First, a superset of information nuggets from the texts is extracted using existing extractors such as named entity recognizers. Then, the extractions are interactively matched to a structured table definition as requested by the user based on embeddings. In our evaluation, we show that WannaDB is thus able to extract structured data from a broad range of (real-world) text collections in high quality without the need to design extraction pipelines upfront.

2023-01-01T00:00:00Z Köhnen, Christoph http://dl.gi.de/handle/20.500.12116/40389 2023-02-23T14:00:24Z 2023-01-01T00:00:00Z

Witness Generation for JSON Schema Patterns Köhnen, Christoph König-Ries, Birgitta; Scherzinger, Stefanie; Lehner, Wolfgang; Vossen, Gottfried JSON Schema is a schema language for the popular data exchange format JSON. This paper introduces an approach to convert regular expressions, which appear in ECMA-262 syntax in JSON Schema, into an alternative syntax such that they may be compiled to finite-state automata.This is a step towards generating witnesses, i.e., JSON instances which are valid w.r.t. the given JSON Schema specification. Specifically, we address the challenge that the ECMA-262 pattern syntax uses anchor symbols to mark the beginning and end of a word, which is not compatible with available libraries for automata manipulation. We implement an algorithm proposed by Dominik Freydenberger to convert regular expressions into brics syntax. We show that we successfully address over 97% of the patterns found in a collection of thousands of JSON Schema specifications collected from GitHub.

2023-01-01T00:00:00Z