A New Algorithm for Faster Mining of Generalized Association Rules. - Jochen Hipp; Andreas Myka; Rüdiger Wirth; Ulrich Güntzer (PKDD, 1998)

Analysing Warranty Claims of Automobiles; An Application Description Following the CRISP-DM Data Mining Process. - Jochen Hipp; Guido Lindner (ICSC, 1999)

Mining Association Rules: Deriving a Superior Algorithm by Analyzing Today's Approaches. - Jochen Hipp; Ulrich Güntzer; Gholamreza Nakhaeizadeh (PKDD, 2000)

Multisensor obstacle detection and tracking. - Christoph Stiller; Jochen Hipp; C. Rössig; A. Ewald (Image Vis. Comput., 2000)

Algorithms for Association Rule Mining - A General Survey and Comparison. - Jochen Hipp; Ulrich Güntzer; Gholamreza Nakhaeizadeh (SIGKDD Explor., 2000)

Data Quality Mining - Making a Virute of Necessity. - Jochen Hipp; Ulrich Güntzer; Udo Grimmer (DMKD, 2001)

Integrating Association Rule Mining Algorithms with Relational Database Systems. - Jochen Hipp; Ulrich Güntzer; Udo Grimmer (ICEIS (1), 2001)

Data Mining of Association Rules and the Process of Knowledge Discovery in Databases. - Jochen Hipp; Ulrich Güntzer; Gholamreza Nakhaeizadeh (ICDM, 2002)

Efficient Rule Retrieval and Postponed Restrict Operations for Association Rule Mining. - Jochen Hipp; Christoph Mangold; Ulrich Güntzer; Gholamreza Nakhaeizadeh (PAKDD, 2002)

Is pushing constraints deeply into the mining algorithms really what we want?: an alternative approach for association rule mining. - Jochen Hipp; Ulrich Güntzer (SIGKDD Explor., 2002)

Wissensentdeckung in Datenbanken mit Assoziationsregeln: Verfahren zur effizienten Regelgenerierung und deren Integration in den Wissensentdeckungsprozeß. - Jochen Hipp (AKA, 2003)

Data Mining: The Next Generation. - Raghu Ramakrishnan 001; Rakesh Agrawal 001; Johann-Christoph Freytag; Toni Bollinger; Christopher W. Clifton; Saso Dzeroski; Jochen Hipp; Daniel A. Keim; Stefan Kramer 001; Hans-Peter Kriegel; Ulf Leser; Bing Liu 001; et al. (Perspectives Workshop: Data Mining: The Next Generation, 2004)

Outlier Detection by Rareness Assumption. - Tomas Hrycej; Jochen Hipp (GI Jahrestagung (1), 2004)

Regelbasierte Ausreißersuche zur Datenqualitätsanalyse. - Joachim Kübart; Udo Grimmer; Jochen Hipp (Datenbank-Spektrum, 2005)

Mining Sequences of Temporal Intervals. - Steffen Kempe; Jochen Hipp (PKDD, 2006)

FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns. - Steffen Kempe; Jochen Hipp; Rudolf Kruse (GfKl, 2007)

Rule-Based Measurement Of Data Quality In Nominal Data. - Jochen Hipp; Markus Müller 004; Johannes Hohendorff; Felix Naumann (ICIQ, 2007)

Mining Frequent Temporal Patterns in Interval Sequences. - Steffen Kempe; Jochen Hipp; Carsten Lanquillon; Rudolf Kruse (Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2008)

Interactivity Closes the Gap - Lessons Learned in an Automotive Industry Application. - Axel Blumenstock; Markus Mueller; Carsten Lanquillon; Steffen Kempe; Jochen Hipp; Rüdiger Wirth (Data Mining for Business Applications, 2010)

Video based localization for Bertha. - Julius Ziegler; Henning Lategahn; Markus Schreiber; Christoph Gustav Keller; Carsten Knöppel; Jochen Hipp; Martin Haueis; Christoph Stiller (Intelligent Vehicles Symposium, 2014)

Making Bertha Drive - An Autonomous Journey on a Historic Route. - Julius Ziegler; Philipp Bender; Markus Schreiber; Henning Lategahn; Tobias Strauss; Christoph Stiller; Thao Dang 002; Uwe Franke; Nils Appenrodt; Christoph Gustav Keller; Eberhard Kaus; Ralf G. Herrtwich; et al. (IEEE Intell. Transp. Syst. Mag., 2014)

Deriving HD maps for highly automated driving from vehicular probe data. - Kay Massow; Birgit Kwella; Niko Pfeifer; Florian Hausler; Jens Pontow; Ilja Radusch; Jochen Hipp; Frank Dölitzscher; Martin Haueis (ITSC, 2016)

CPD: Crowd-based Pothole Detection. - Florian Wirthmueller; Jochen Hipp; Kai-Uwe Sattler; Manfred Reichert (VEHITS, 2019)

Towards Incorporating Contextual Knowledge into the Prediction of Driving Behavior. - Florian Wirthmüller; Julian Schlechtriemen; Jochen Hipp; Manfred Reichert (ITSC, 2020)

A Fleet Learning Architecture for Enhanced Behavior Predictions during Challenging External Conditions. - Florian Wirthmüller; Marvin Klimke; Julian Schlechtriemen; Jochen Hipp; Manfred Reichert (SSCI, 2020)

The Atlas of Lane Changes: Investigating Location-Dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet. - Florian Wirthmüller; Jochen Hipp; Christian Reichenbächer; Manfred Reichert (ITSC, 2021)

Predicting the Time Until a Vehicle Changes the Lane Using LSTM-Based Recurrent Neural Networks. - Florian Wirthmüller; Marvin Klimke; Julian Schlechtriemen; Jochen Hipp; Manfred Reichert (IEEE Robotics Autom. Lett., 2021)

Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction Using Large Data Sets. - Florian Wirthmüller; Julian Schlechtriemen; Jochen Hipp; Manfred Reichert (IEEE Trans. Intell. Transp. Syst., 2021)

Identifying Scenarios in Field Data to Enable Validation of Highly Automated Driving Systems. - Christian Reichenbächer; Maximilian Rasch; Zafer Kayatas; Florian Wirthmüller; Jochen Hipp; Thao Dang 002; Oliver Bringmann 001 (VEHITS, 2022)

Statistical Modelling of Driving Scenarios in Road Traffic using Fleet Data of Production Vehicles. - Christian Reichenbächer; Jochen Hipp; Oliver Bringmann 001 (CoRR, 2024)

Estimating the Joint Probability of Scenario Parameters with Gaussian Mixture Copula Models. - Christian Reichenbächer; Philipp Rank; Jochen Hipp; Oliver Bringmann 001 (CoRR, 2025)