Relaxation of Subgraph Queries Delivering Empty Results

Graph databases with the property graph model are used in multiple domains including social networks, biology, and data integration. They provide schema-flexible storage for data of a different degree of a structure and support complex, expressive queries such as subgraph isomorphism queries. The exibility and expressiveness of graph databases make it difficult for the users to express queries correctly and can lead to unexpected query results, e.g. empty results. Therefore, we propose a relaxation approach for subgraph isomorphism queries that is able to automatically rewrite a graph query, such that the rewritten query is similar to the original query and returns a non-empty result set. In detail, we present relaxation operations applicable to a query, cardinality estimation heuristics, and strategies for prioritizing graph query elements to be relaxed. To determine the similarity between the original query and its relaxed variants, we propose a novel cardinality-based graph edit distance. The feasibility of our approach is shown by using real-world queries from the DBpedia query log

DebEAQ - debugging empty-answer queries on large data graphs

The large volume of freely available graph data sets impedes the users in analyzing them. For this purpose, they usually pose plenty of pattern matching queries and study their answers. Without deep knowledge about the data graph, users can create ‘failing’ queries, which deliver empty answers. Analyzing the causes of these empty answers is a time-consuming and complicated task especially for graph queries. To help users in debugging these ‘failing’ queries, there are two common approaches: one is focusing on discovering missing subgraphs of a data graph, the other one tries to rewrite the queries such that they deliver some results. In this demonstration, we will combine both approaches and give the users an opportunity to discover why empty results were delivered by the requested queries. Therefore, we propose DebEAQ, a debugging tool for pattern matching queries, which allows to compare both approaches and also provides functionality to debug queries manually

Combining Flexible Queries and Knowledge Anchors to facilitate the exploration of Knowledge Graphs

Semantic web and information extraction technologies are enabling the creation of vast information and knowledge repositories, particularly in the form of knowledge graphs comprising entities and the relationships between them. Users are often unfamiliar with the complex structure and vast content of such graphs. Hence, users need to be assisted by tools that support interactive exploration and flexible querying. In this paper we draw on recent work in flexible querying for graph-structured data and identifying good anchors for knowledge graph exploration in order to demonstrate how users can be supported in incrementally querying, exploring and learning from large complex knowledge graphs. We demonstrate our techniques through a case study in the domain of lifelong learning and career guidance

Stochastic Resonance in Underdamped, Bistable Systems

We carry out a detailed numerical investigation of stochastic resonance in underdamped systems in the non-perturbative regime. We point out that an important distinction between stochastic resonance in overdamped and underdamped systems lies in the lack of dependence of the amplitude of the noise-averaged trajectory on the noise strength, in the latter case. We provide qualitative explanations for the observed behavior and show that signatures such as the initial decay and long-time oscillatory behaviour of the temporal correlation function and peaks in the noise and phase averaged power spectral density, clearly indicate the manifestation of resonant behaviour in noisy, underdamped bistable systems in the weak to moderate noise regime.Comment: Revtex; (10+8)pp including 8 figure