Ontology learning is the process of acquiring (constructing or integrating) an ontology (semi-
) automatically. Being a knowledge acquisition task, it is a complex activity, which becomes …

Distance-based algorithms are widely used for data classification problems. The k-nearest
neighbour classification (k-NN) is one of the most popular distance-based algorithms. This …

Artificial Intelligence federates numerous scientific fields in the aim of develo** machines
able to assist human operators performing complex treatments---most of which demand high …

An ontology is an explicit formal conceptualization of some domain of interest. Ontologies
are increasingly used in various fields such as knowledge management, information …

Supervised training procedures for semantic parsers produce high-quality semantic parsers,
but they have difficulty scaling to large databases because of the sheer number of logical …

A large number of information systems use many different individual schemas to represent
data. Semantically linking these schemas is a necessary precondition to establish …

Due to the recent explosion of the amount of on-line accessible biomedical data and tools,
finding and retrieving the relevant information is not an easy task. The vision of a Semantic …

Representing knowledge about researchers and research communities is a prime use case
for distributed, locally maintained, interlinked and highly structured information in the spirit of …

Semantic measures are widely used today to estimate the strength of the semantic
relationship between elements of various types: units of language (eg, words, sentences …

Common user-and business-requirements demand an integrated view on the multitude of
available information resources that are processed in a variety of heterogeneous information …