Espresso: Explaining Relationships between Entity Sets

Espresso is a system to compute semantically meaningful substructures (so-called relatedness cores) from a knowledge graph. The purpose of the system is to answer questions of the form «Which European politicians are related to politicians in the United States and how?» or «How can one summarize the relationship between China and countries from the Middle East over the last five years?» In this setting, a question is specified by means of two sets of query entities. These sets (e.g. "European politicians" or "United States politicians") can be determined by an initial graph query over a knowledge graph capturing relationships between real-world entities. As a next step, we analyze the (indirect) relationships that connect entities from both sets (e. g. membership in organizations, statements made on TV, etc.), generate an informative and concise result, and finally provide a user-friendly explanation of the answer. As output, we aim to return concise subgraphs corresponding to important event complexes, that connect entities from the two sets and explain their relationships. Espresso provides a user interface for the specification of entity sets, computes informative relatedness cores that summarize the relationship between the query entities, and finally displays a visually appealing visualization of the extracted subgraph to the user. Applications of the proposed system include scenarios that require to provide background information on the current state-of-affairs between real-world entities such as politicians, organizations, and the like, e. g. to a journalist preparing an article involving the entities of interest.

• Espresso: Explaining Relationships between Entity Sets
  Stephan Seufert, Klaus Berberich, Srikanta J. Bedathur, Sarath Kumar Kondreddi, Patrick Ernst, and Gerhard Weikum
  Proceedings of the 25th International Conference on Information and Knowledge Management (CIKM 2016),
  Indianapolis, IN, United States, October 24-28, 2016. ACM.
• Instant Espresso: Interactive Analysis of Relationships in Knowledge Graphs (Demo)
  Stephan Seufert, Patrick Ernst, Srikanta J. Bedathur, Sarath Kumar Kondreddi, Klaus Berberich, and Gerhard Weikum
  Proceedings of the 25th International World Wide Web Conference (WWW 2016),
  Montreal, QC, Canada, April 11-15, 2016. ACM.
• Efficient Computation of Relationship-Centrality in Large Entity-Relationship Graphs (poster) 
  Stephan Seufert,  Srikanta J. Bedathur, Johannes Hoffart, Andrey Gubichev, and Klaus Berberisch
  Posters and Demonstrations Track of the 12th International Semantic Web Conference (ISWC 2013),
  Sydney, NSW, Australia, October 21-25, 2013.