2 citations · 4 across the 4 of their papers we have counts for
4 papers
CURED: Creating, Understanding, and Repairing Errors Demonstrator
Nicholas Chandler, Sebastian Jäger, Philipp Jung +1
Detecting and cleaning errors in tabular data is a prerequisite for data intense software applications. Recent research at the intersection of Machine Learning (ML) and Database Ma…
Automated Extraction of Fine-Grained Standardized Product Information from Unstructured Multilingual Web Data
Alexander Flick, Sebastian Jäger, Ivana Trajanovska +1
Extracting structured information from unstructured data is one of the key challenges in modern information retrieval applications, including e-commerce. Here, we demonstrate how r…
GreenDB -- A Dataset and Benchmark for Extraction of Sustainability Information of Consumer Goods
Sebastian Jäger, Alexander Flick, Jessica Adriana Sanchez Garcia +3
The production, shipping, usage, and disposal of consumer goods have a substantial impact on greenhouse gas emissions and the depletion of resources. Machine Learning (ML) can help…
GreenDB: Toward a Product-by-Product Sustainability Database
Sebastian Jäger, Jessica Greene, Max Jakob +3
The production, shipping, usage, and disposal of consumer goods have a substantial impact on greenhouse gas emissions and the depletion of resources. Modern retail platforms rely h…