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 …

Automated legal text classification is a prominent research topic in the legal field. It lays the
foundation for building an intelligent legal system. Current literature focuses on international …

In 2004 we published in this journal an article describing OntoLearn, one of the first systems
to automatically induce a taxonomy from documents and Web sites. Since then, OntoLearn …

Automatic term extraction (ATE) is a Natural Language Processing (NLP) task that eases the
effort of manually identifying terms from domain-specific corpora by providing a list of …

In this paper we present a graph-based approach aimed at learning a lexical taxonomy
automatically starting from a domain corpus and the Web. Unlike many taxonomy learning …

In this paper we present a framework for the automatic building of a domain taxonomy from
text corpora, called Automatic Taxonomy Construction from Text (ATCT). This framework …

This paper proposes a framework to automatically construct taxonomies from a corpus of text
documents. This framework first extracts terms from documents using a part-of-speech …

Applications related to domain specific text processing often use glossaries and ontologies,
and the main step of such resource construction is term recognition. This paper presents a …

The need for interoperable semantics in modern information systems forces to develop more
and more intelligent solutions. The increasing demand for these solutions, the explosion of …

The inconsistency of data terminology has imposed big challenges on integrating
transportation project data from distinct sources. Differences in meaning of data elements …