Automatizing the merging of knowledgebases is an important step towards more efficient knowledge management. The cases when two knowledgebases need to be merged completely into a monolithic result, however, are relatively rare. Most often, some of the information is irrelevant, not trusted, or needs special treatment as a belief, opinion or preference. This paper presents an approach for partia...

Droplet manipulation is comprised of techniques such as droplet generation, merging, and splitting, of which droplet merging is one of the major bottlenecks in achieving high-throughput analysis. Here we present a three dimensional electrode that improves the electric field uniformity and field strength experienced by two adjacent droplets undergoing merging. We conducted a systematic compariso...

Abstract Bayesians often appeal to “merging of opinions” rebut charges excessive subjectivity. But what happens in the short run is greater interest than limit. Seidenfeld and coauthors use this observation as motivation for investigating counterintuitive phenomenon dilation, since, they allege, dilation “the opposite” asymptotic merging opinions. The measure uncertainty relevant however, not o...

Latest research efforts on the semi-automatic coordination of ontologies “touch” on the mapping /merging of ontologies using the whole breadth of available knowledge. Addressing this issue, this paper presents the HCONE-merge approach, which is further extended towards automating the merging process. HCONE-merge makes use of the intended informal meaning of concepts by mapping them to WordNet s...

We present ALA, a tool for the automatic lexical annotation (i.e. annotation w.r.t. a thesaurus/lexical resource) of structured and semi-structured data sources and the discovery of probabilistic lexical relationships in a data integration environment. ALA performs automatic lexical annotation through the use of probabilistic annotations, i.e. an annotation is associated to a probability value....

Ontologies have been largely used to represent terminological knowledge, specially with the advent of the Semantic Web. As knowledge is not static, it is crucial to learn how to deal with ontology dynamics, which includes Ontology Merging and Debugging. Basically, we want to deal with the inconsistencies and incoherences that may occur when a knowledge base receives a new information or when tw...

When comparing different grammatical inference algorithms, it becomes evident that generic techniques have been used in different systems. Several finite-state learning algorithms use state-merging as their underlying technique and a collection of grammatical inference algorithms that aim to learn context-free grammars build on the concept of substitutability to identify potential grammar rules...

We combine argumentation, belief revision and description logic ontologies for extending the δ-ontologies framework to show how to merge two ontologies in which the union of the strict terminologies could lead to inconsistency. To solve this problem, we revisit a procedure presented by Falappa et al. in which part of the offending terminologies are turned defeasible by using a kernel revision o...