For bachelor students we offer German lectures on database systems in addition with paper- or project-oriented seminars. Within a one-year bachelor project students finalize their studies in cooperation with external partners. For master students we offer courses on information integration, data profiling, search engines and information retrieval enhanced by specialized seminars, master projects and advised master theses.
The Web Science group focuses on various topics related to the Web, such as Information Retrieval, Natural Language Processing, Data Mining, Knowledge Discovery, Social Network Analysis, Entity Linking, and Recommender Systems. The group is particularly interested in Text Mining to deal with the vast amount of unstructured and semi-structured information available on the Web.
Most of our research is conducted in the context of larger research projects, in collaboration across students, across groups, and across universities. We strive to make available most of our data sets and source code.
Former PhD student of the HPI Research School at University of Potsdam Email: Johannes Lorey
Large-Scale Data Analysis and Processing
Linked Data Management
Caching and Prefetching Strategies for SPARQL Queries
Lorey, Johannes; Naumann, Felix
Proceedings of the 3rd International Workshop on Usage Analysis and the Web of Data (USEWOD)
Selected as Best Workshop Paper for publication in ESWC post-proceedings
Linked Data repositories offer a wealth of structured facts, useful for a wide array of application scenarios. However, retrieving this data using SPARQL queries yields a number of challenges, such as limited endpoint capabilities and availability, or high latency for connecting to it. To cope with these challenges, we argue that it is advantageous to cache data that is relevant for future information needs. However, instead of only retaining results of previously issued queries, we aim at retrieving data that is potentially interesting for subsequent requests in advance. To this end, we present different methods to modify the structure of a query so that the altered query can be used to retrieve additional related information. We evaluate these approaches by applying them to requests found in real-world SPARQL query logs.