Search Results

Previous literature has shown that it is possible to align word embeddings from different languages with unsupervised methods based on a distance-preserving mapping, with the assumption that the embeddings are isometric. However, these methods ...

In this article, we compare the use of Redescription Mining (RM) and Association Rule Mining (ARM) for discovering class definitions in Linked Open Data (LOD). RM is aimed at mining alternate descriptions from two datasets related to the same set ...

To some extent, texts can be represented in the form of graphs, such as dependency graphs in which nodes represent words and edges represent grammatical dependencies between words. Graph representation of texts is an interesting alternative to string ...

Social semantic web creates read/write spaces where users and smart agents collaborate to produce knowledge readable by humans and machines. An important issue concerns the ontology evolution and evaluation in man-machine collaboration. How to perform a ...

One way of processing case retrieval in a case-based reasoning (CBR) system is using an ontology in order to generalise the target problem in a progressive way, then adapting the source cases corresponding to the generalised target problem. This paper ...

Semantic wikis enable collaboration between human agents for creating knowledge systems. In this way, data embedded in semantic wikis can be mined and the resulting knowledge patterns can be reused to extend and improve the structure of wikis. This ...

In this paper we discuss the problem of extracting and evaluating associations between drugs and adverse effects in pharma-covigilance data. Approaches proposed by the medical informatics community for mining one drug - one effect pairs perform an ...

In this paper we discuss the problem of extracting and evaluating associations between drugs and adverse effects in pharma-covigilance data. Approaches proposed by the medical informatics community for mining one drug - one effect pairs perform an ...

In this paper we discuss the problem of extracting and evaluating associations between drugs and adverse effects in pharmacovigilance data. Approaches proposed by the medical informatics community for mining one drug - one effect pairs perform an ...

This paper addresses the issue of adapting cases represented by plain text with the help of formal concept analysis and natural language processing technologies. The actual cases represent recipes in which we classify ingredients according to culinary ...

In pharmacovigilance, linking the adverse reactions by patients to drugs they took is a key activity typically based on the analysis of patient reports. Yet generating potentially interesting pairs (drug, reaction) from a record database is a complex ...

Building a domain ontology usually requires several resources of different types, e.g. thesaurus, object taxonomies, terminologies, databases, sets of documents, etc, where objects are described in terms of attributes and relations with other objects. ...

PACTOLE stands for "Property And Class characterization from Text for OntoLogy Enrichment" and is a semi-automatic methodology for enriching an initial ontology from a collection of texts in a given domain. PACTOLE is also the name of the associated ...

Building a domain ontology usually requires several resources of different types, e.g. thesaurus, object taxonomies, terminologies, data-bases, sets of documents, etc. where objects are described in terms of attributes and relations with other objects. ...

We propose an approach for semi-automated construction of ontologies from text whose core component is a Relational Concept Analysis (RCA) framework which extends Formal Concept Analysis (FCA), a lattice-theory paradigm for discovering abstractions ...

This paper presents a methodology for the semantic annotation of web pages with individuals of a domain ontology. While most semantic annotation systems can recognize knowledge units, they usually do not establish explicit relations between them. The ...

In this paper, we present research trends carried out in the Orpailleur team at loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge discovery in databases process (kdd) consists in processing a huge ...

In this paper, we present research trends carried out in the Orpailleur team at loria, showing how knowledge discovery and knowledge processing may be combined. The knowledge discovery in databases process (KDD) consists in processing a huge volume of ...

This paper proposes a methodology for text mining relying on the classical knowledge discovery loop, with a number of adaptations. First, texts are indexed and prepared to be processed by frequent itemset levelwise search. Association rules are then ...

We introduce the application of text categorization techniques to the astronomy field to work out semantic ambiguities between table column's names. In the astronomy field, astronomers often assign different names to table columns at their will even if ...