Maik Fröbe

Researcher and PhD candidate

Maik Fröbe studied computer science (M.Sc.) at the university of Leipzig. Since February 2019 he was a researcher in the big data analytics group at the institute for computer science of the Martin-Luther-Universität Halle-Wittenberg, and now since 2022 he is at the chair for databases and information systems. The group is part of the Webis GroupExternal link.

His current research interests lie in the areas of information retrieval, machine learning and big data—in particular near-duplicate detection in web archivesExternal link and learning to rank.

Research

Teaching

Supervised theses:

Karl Hase. Statistical Bootstrap Tests with Redundant Data
Max Henze. Simulation von Suchanfragen durch Anchortext
Simon Reich. Integrating Information Retrieval Toolkits into TIRA
Jan Heinrich Reimer. Identifying and Answering Health-Related Questions
Danik Hollatz. Precision-Oriented Argument Retrieval
Wilhelm Beiche. Kontextabhängige Termgewichtung für Total-Recall-Suchen
Adrien Klose. Multi-Task-Learning mit Transformer-Modellen für die Ad-Hoc-Suche mittels Information-Retrieval-Axiomen
Nicola Lea Libera. The Performance of Human Query Obfuscation - A Gamified Approach
Maximilian Probst. MS-Anchor: Linktexte als Ranking-Features im Zeitalter von Deep Learning
Paul Alexander Cahn. Total Recall via Keyqueries: A Case Study for Systematic Reviews
Johannes Huck. Keyqueries zur Erweiterung von Suchanfragen mit explizitem Relevanz-Feedback
Daniel Wächtler. Automatische Erzeugung von Ground-Truth-Daten für Learning to Rank aus Twitter-Crawls
Eric Oliver Schmidt. Crypsor: Automatische Verschleierung sensibler Suchanfragen
Jan Philipp Bittner. Evaluation of Ad-Hoc Information Retrieval Systems on Web Crawls with Redundant Documents
Jan Heinrich Reimer. Bias in Learning to Rank Caused by Redundant Web Documents
Nina Katharina Schwanke. Entwicklung und Evaluierung einer Suchmaschine für Polizeipressemitteilungen

Maik Fröbe

Research

Teaching

Links