Ontologies are often viewed as the answer to the need for interoperable semantics in
modern information systems. The explosion of textual information on the Read/Write Web …

Semantic web technologies have shown their effectiveness, especially when it comes to
knowledge representation, reasoning, and data integration. However, the original semantic …

Criminal analysis is a complex process involving information gathered from different
sources, mainly of quantitative character, such as billings or bank account transactions, but …

We present a methodology for learning a taxonomy from a set of text documents that each
describes one concept. The taxonomy is obtained by clustering the concept definition …

The process of converting natural language specifications into conceptual models requires
detailed analysis of natural language text, and designers frequently make mistakes when …

Abstract The goal of Ontology Learning from Text is to learn ontologies that represent
domains or applications that change often. Manually learning and updating such ontologies …

Many existing methods for bilingual lexicon learning from comparable corpora are based on
similarity of context vectors. These methods suffer from noisy vectors that greatly affect their …

Ontology learning techniques are based on extensive basic knowledge, from unstructured
data to structured data. Creating an ontology manually is undoubtedly a time consuming …

Banks are faced with the challenge of adapting to the ever-changing risk and methods
related to money laundering. Money laundering is a complex, dynamic and distributed …

Ontologies constitute an exciting model for representing a domain of interest, since they
enable information-sharing and reuse. Existing inference machines can also use them to …