Graph Management and Mining
complex data and relationships using graphs has become ubiquitous in
many emerging disciplines such as computational biology, social and
communication networking, and scientific data management in general.
Several novel methods for managing and mining graph data have been
developed to address the steadily increasing amount and complexity of
graph data. While many theoretical aspects such as graph isomorphism and
partitioning have been studied extensively in graph theory and related
fields, new aspects arise from an application point of view. The
objective of this seminar is to get an overview of the most recent
developments in the field of graph management and graph mining with a
particular focus on massive graph data.
- Graph Indexing and Summarization
- Graph Query Languages
- Graph Similarity
- Graph Clustering
- Graph Classification
- Mining Graph Patterns
- Mining Geometric Graphs
- Mining Streaming Graph Data
Seminar: Thursdays, 2-4pm, INF 368, Room 248
First meeting: Thursday, April 14, 2pm, INF 368, Room 248
Data Mining, Algorithms and Data Structures, Efficient Algorithms
Information about the seminar topics and corresponding literature
(conference and journal papers) will be given during the first meeting.
All papers will also be distributed through the Moodle Web-site for this
In order to receive the 4 ECST
for this seminar, students have to (1) participate in all presentations,
(2) give a presentation (about 40 minutes), and (3) prepare a technical
report covering the topic they presented in the seminar. More details
will be given during the first meeting.
Students with Computer Science (Informatik) as major or minor.
Prof. Dr. Michael Gertz, email@example.com, INF 348, Room 12b. All material related to this seminar will be provided through the Moodle Web-site for this seminar; see also http://elearning.uni-heidelberg.de/course/category.php?id=4807.