Catching Numeric Inconsistencies in Graphs

Catching Inconsistencies with the Semantic Web: A Biocuration Case Study

Background The UniProtKB/Swiss-Prot database is manually curated by a team of experienced biocurators with the aim to provide to the scientific community high-quality information on proteins. Ensuring a high-quality curation standard depends in part on effective tools that help curators to avoid trivial mistakes during data curation. Description We describe here a system that is using SPARQL qu...

Handling Numeric Criteria in Relaxed Planning Graphs

Nowadays, one of the main techniques used in heuristic planning is the generation of a relaxed planning graph, based on a Graphplan-like expansion. Planners like FF or MIPS use this type of graphs in order to compute distance-based heuristics during the planning process. This paper presents a new approach to extend the functionality of these graphs in order to manage numeric optimization criter...

Catching a Fast Robber on Interval Graphs

We analyse the Cops and ∞-fast Robber game on the class of interval graphs and prove it to be polynomially decidable on such graphs. This solves an open problem posed in paper “Pursuing a fast robber on a graph” by Fomin et al. [4] The game is known to be already NP-hard on chordal graphs and split-graphs. The game is played by two players, one controlling k cops, the other a robber. The player...

Finding the Most Descriptive Substructures in Graphs with Numeric Labels

Many graph datasets are labelled with numeric attributes. Frequent substructure discovery algorithms usually ignore these attributes; in this paper we show that they can be used to improve discrimination and search performance. Our thesis is that the most descriptive substructures are those which are normative both in terms of their structure and in terms of their numeric values. We propose an ...

Catching Kangaroos in Function Fields Catching Kangaroos in Function Fields