Bilingual lexicons are central components of machine translation and cross-lingual information retrieval systems. Their manual construction requires strong expertise in both languages involved and is a costly process. Several automatic methods were proposed as an alternative but they often rely on resources available in a limited number of languages and their performances are still far behind t...

This paper describes the FACT system for knowledge discovery from text. It discovers associations − patterns of co-occurrence − amongst keywords labeling the items in a collection of textual documents. In addition, FACT is able to use background knowledge about the keywords labeling the documents in its discovery process. FACT takes a query-centered view of knowledge discovery, in which a disco...

Most existing inductive learning systems form concept descriptions in propositional languages from vectors of basic features. However, many concepts are characterized by the relationships of individual examples to general domain knowledge. We describe a system that constructs relational terms e ciently to augment the description language of standard inductive systems. In our approach, examples ...

This paper presents the automatic summarization problem and specifies a generic process for the automatic construction of summaries. Most recent approaches to summarization are exposed as contributions to the various steps of this process. The paper elaborates on the grounds of multi-document automatic summarization and examines the use of background knowledge, indicating related, ongoing and r...

We investigate the use of a background knowledge ontology in ontology matching. We conducted experiments on matching two medical ontologies using a third extensive one as background knowledge, and compare the results with directly matching the two ontologies. Our results indicate that using background knowledge, in particular the exploitation of its structure, has enormous benefits on the match...

A large amount of transaction data containing associations between individuals and sensitive information flows everyday into data stores. Examples include web queries, credit card transactions, medical exam records, transit database records. The serial release of these data to partner institutions or data analysis centers is a common situation. In this paper we show that, in most domains, corre...

“Tell me who your friends are, and I will tell you who you are” – this proverb best illustrates our approach to the normalization of gene names. In this approach, we rely on background knowledge that describes various aspects of a gene: it is localized on a chromosomal band, it belongs to an operon structure, it is a member of a gene family, its products take part in biological processes, they ...

When using data mining to find regularities in data, the obtained results (or patterns) need to be interpreted. The explanation of such patterns is achieved using the background knowledge which might be scattered among different sources. This intensive process is usually committed to the experts in the domain. With the rise of Linked Data and the increasing number of connected datasets, we assu...

Background knowledge from Linked Open Data sources, such as DBpedia, Eurostat, and GADM, can be used to create both interpretations and advanced visualizations of statistical data. In this paper, we discuss methods of linking statistical data to Linked Open Data sources and the use of the Explain-a-LOD toolkit. The paper further shows exemplary findings and visualizations created by combining t...