An interdisciplinary project in collaboration with VDE, Tübingen and Köln universities. It shed light on the role of AI data from a legal, ethical, informational and practical perspective. KITQAR is funded by Federal Ministry of Labour and Social Affairs from Dec. 2021 to Jul. 2023.
Real estate Rating
Rating the value of a real-estate is a complex process relying on local and global properties. The IREBS of the University of Regensburg and HPI's Information Systems and the Algorithm Engineering groups collaborate to automate real-estate valuation by means of data engineering and artificial intelligence. The project is funded by Deutscher Sparkassenverlag from July 2020 to September 2021
Relational Header Discovery
Column headers are among the most relevant types of meta-data for relational tables, because they provide meaning and context in which the data is to be interpreted. Unfortunately, in many cases column headers are missing. We introduce a fully automated, multi-phase system that discovers table column headers where headers are missing, meaningless, or not representative for the column values.
Among the most important types of metadata is the number of distinct values in a column, also known as the zeroth-frequency moment. Cardinality estimation itself has been an active research topic in the past decades due to its many applications. The aim of this work is to review the literature of cardinality estimation and to present a detailed experimental study of twelve algorithms, scaling far beyond the original experiments.