Resource-efficient Graph Mining (A06)

• Subject Area: Theoretical Computer Science ; Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: from 2015 to 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 124020371

Linked data and networks occur often in the context of embedded systems. Sensors, RFID-chips, cameras, etc. of products of our daily life continuously produce data and communicate with each other as well as the user. A natural representation of linked data are graphs where objects correspond to the vertices of the graph and the links to its edges. In this project, we will develop new approaches and algorithms for the classification of graphs and linked data sets under resource constraints. To this aim, randomized approaches from algorithmic theory, approaches for mining and learning with graphs (in particular graph kernels) and algorithmic engineering approaches will be combined.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 876: Providing Information by Resource-Constrained Data Analysis
• Applicant Institution: Technische Universität Dortmund
• Project Heads: Professor Dr. Johannes Christian Fischer, since 5/2020; Professor Dr. Kristian Kersting, until 4/2017; Dr. Nils Kriege, from 7/2018 until 4/2020; Professorin Dr. Petra Mutzel, until 9/2019; Professor Dr. Christian Sohler, until 12/2018; Privatdozent Dr. Frank Weichert, since 1/2019