Knowledge Graphs are a universal and versatile mechanism of knowledge representation on the Web. In the past years, large-scale, publicly available Knowledge Graphs, such as DBpedia or Wikidata, have gained momentun in various applications. The aim of this seminar is to get an overview of existing Knowledge Graphs, the underyling techniques for their creation and development, as well as potential use cases.
In this seminar, you will familiarize yourself with a knowledge graph both by reading scientific papers and technical reports, as well as experimentation and exploration on your own. We will analyze strenghts and weaknesses of current approaches, discuss commonalities and particularities of the different knowledge graphs, and explore current research directions.
As a participant, you are supposed to introduce one knowledge graph in a seminar paper, and present it to the seminar participants. Each seminar paper undergoes a peer review process in the seminar. Presentations are supposed to be about 25 minutes long.
There will be four dates with three presentations each:
Note: The list below only lists the main paper(s) introducing the knowledge graph as an entry point to your work. It is part of your task to dig deeper by reading cited and citing sources as well.
|DBpedia||Lehmann, Jens, et al. DBpedia–A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia.|
|YAGO||Mahdisoltani, Farzaneh, Joanna Biega, and Fabian M. Suchanek. Yago3: A knowledge base from multilingual wikipedias.|
|Wikidata||Vrandečić, Denny, and Markus Krötzsch. Wikidata: a free collaborative knowledgebase|
|Probase||Wu, Wentao, et al. Probase: A probabilistic taxonomy for text understanding|
|WebIsA||Seitner, Julian, et al. A Large DataBase of Hypernymy Relations Extracted from the Web|
|NELL||Carlson, Andrew, et al. Coupled semi-supervised learning for information extraction|
|Knowledge Vault||Dong, Xin, et al. Knowledge vault: A web-scale approach to probabilistic knowledge fusion|
|DeepDive||Shin, Jaeho, et al. Incremental knowledge base construction using deepdive|
|DIADEM||Furche, Tim, et al. DIADEM: thousands of websites to a single database|
|ConceptNet||Speer, Robert, and Catherine Havasi. Representing General Relational Knowledge in ConceptNet 5|
|BabelNet||Navigli, Roberto, and Simone Paolo Ponzetto. BabelNet: Building a very large multilingual semantic network|
|Cyc||Lenat, Douglas B. CYC: A large-scale investment in knowledge infrastructure|
||Etzioni, Oren, et al. Open information extraction: The second generation|
The following reading list collects basic introductions and surveys on the seminar topic. Every participant of the seminar is expected to familiarize themselves with those papers.