Extending ontologies by finding siblings using set expansion techniques

Motivation: Ontologies are an everyday tool in biomedicine to capture and represent knowledge. However, many ontologies lack a high degree of coverage in their domain and need to improve their overall quality and maturity. Automatically extending sets of existing terms will enable ontology engineers to systematically improve text-based ontologies level by level

Intra-radicular dentin treatments and retention of fiber posts with self-adhesive resin cements

The aim of this study was to evaluate the effect of treating intraradicular dentin with irrigating solutions on the retention of glass-fiber posts luted with self-adhesive resin cement. Bovine incisors were endodontically treated, and 9-mm-deep postholes were prepared. Before inserting the cement, the root canals were irrigated with various solutions: 11.5% polyacrylic acid for 30 s, 17% EDTA for 60 s, or 5% NaOCl for 60 s, respectively. Irrigation with distilled water was used in the control group. After all specimens had been rinsed with distilled water, the excess moisture was removed and the posts were luted using either BisCem (Bisco) or RelyX Unicem clicker (3M ESPE). Seven days after luting, the specimens were sectioned transversally into 1-mm-thick slices, which were submitted to push-out testing on a mechanical testing machine. Bond strength data (n = 6 per group) were analyzed by two-way ANOVA and Student-Newman-Keuls' test (α = 0.05). For Unicem, EDTA showed lower bond strength than the other solutions, which had similar results. For BisCem, EDTA showed higher bond strength than the other treatments, while application of NaOCl yielded higher bond strength than polyacrylic acid whereas the control group had intermediate results. In conclusion, irrigating root canals before insertion of self-adhesive resin cements, especially EDTA, might interfere with retention of the fiber posts

Coupling information extraction and data mining for ontology learning in PARMENIDES

Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions and company values. This information is extracted by pre-processing and querying multiple sources, combining and condensing the findings. It is characteristic that the extraction process is resource intensive and has to be performed regularly and quite frequently. In the research project PARMENIDES, we are developing methods that establish ontologies over an application domain, annotate documents with the ontology components and identify the entities in them, so that we can decompose business into conventional queries towards entities and XML-annotated texts