Data Mining with Linked Open Data (Mine@LOD)

• Applicant: Professor Dr. Heiko Paulheim
• Subject Area: Image and Language Processing, Computer Graphics and Visualisation, Human Computer Interaction, Ubiquitous and Wearable Computing
• Term: from 2013 to 2018
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 238007641

Data Mining is focused on finding patterns and regularities in large data sets. Common approaches assume all of the relevant data is stored in one database or data warehouse, which is then scanned for patterns using machine learning or data mining methods. With a growing development of the Semantic Web and the global availability of public linked data sources, it is an open research question how to leverage those data sources for data mining processes.In many real-world use cases, additional background knowledge is required in order to find relevant and interesting patterns. For example, better explanations for sales figures of books in different book stores can be found when taking into account detail information both on the books (such as their genre) and the neighborhoods of the book stores (such as the population structure). Since it is hardly feasible to provide that background information for all possible use cases, the project Mine@LOD aims at developing approaches for enriching data sets with background knowledge from Linked Open Data in a fully automated way. We expect that with those approaches, existing data mining methods can be significantly improved. To that end, suitable data sources have to be identified, the relevant information within those data sources needs to be located, and existing learning and mining algorithms have to be improved in a way that they can deliver reasonable results in the presence of a large number of weakly relevant data sources.

• DFG Programme: Research Grants