Mapping the forms of meaning in small worlds

International audienceProx is a stochastic method to map the local and global structures of real-world complex networks which are called Small Worlds. Prox transforms a graph into a Markov chain, the states of which are the nodes of the graph in question. Particles wander from one node to another within the graph by following the graph " s edges. It is the dynamics of the particles " trajectories that map the structural properties of the graphs that are studied. Concrete examples are presented in a graph of synonyms to illustrate this approach

PageRank Induced Topology for Real-World Networks

This article presents a stochastic method for studying the structure of large small worlds graphs. The principle of this method is to apply a PageRank-like importance algorithm, with a damping factor and an external importance source. By varying the source vector, one obtains a powerful graph visualization tool, which reveals the structural organization of small worlds graphs

From Random Graph to Small World by Wandering

Numerous studies show that most known real-world complex networks share similar properties in their connectivity and degree distribution. They are called small worlds. This article gives a method to turn random graphs into Small World graphs by the dint of random walks

Clustering Sets of Objects Using Concepts-Objects Bipartite Graphs

International audienceIn this paper we deal with data stated under the form of abinary relation between objects and properties. We propose an approachfor clustering the objects and labeling them with characteristic subsetsof properties. The approach is based on a parallel between formal con-cept analysis and graph clustering. The problem is made tricky due tothe fact that generally there is no partitioning of the objects that can beassociated with a partitioning of properties. Indeed a relevant partitionof objects may exist, whereas it is not the case for properties. In order toobtain a conceptual clustering of the objects, we work with a bipartitegraph relating objects with formal concepts. Experiments on artificialbenchmarks and real examples show the effectiveness of the method,more particularly the fact that the results remain stable when an in-creasing number of properties are shared between objects of differentclusters

A Parallel between Extended Formal Concept Analysis and Bipartite Graphs Analysis

International audienceThe paper offers a parallel between two approaches to con-ceptual clustering, namely formal concept analysis (augmented with theintroduction of new operators) and bipartite graph analysis. It is shownthat a formal concept (as defined in formal concept analysis) correspondsto the idea of a maximal bi-clique, while a “conceptual world” (definedthrough a Galois connection associated of the new operators) is a dis-connected sub-graph in a bipartite graph. The parallel between formalconcept analysis and bipartite graph analysis is further exploited by con-sidering “approximation” methods on both sides. It leads to suggests newideas for providing simplified views of datasets

Semantic associations and confluences in paradigmatic networks

International audienceIn this article, we hypothesize that some of the structural properties of paradigmatic graphs of the hierarchical small world type are to be found in all natural languages. Within this hypothesis of the universal structure of paradigmatic graphs, we explore a method for the automatic analysis of semantic groupings in order to distinguish, on typological and cognitive levels, which groupings are universal, and which are more limited geographically, genetically or culturally

Comparing and Fusing Terrain Network Information

International audienceTerrain networks (or complex networks) is a type of relational infor-mation that is encountered in many fields. In order to properly answer questionspertaining to the comparison or to the merging of such networks, a method thattakes into account the underlying structure of graphs is proposed. The effective-ness of the method is illustrated using real linguistic data networks and artificialnetworks, in particular

Enrichissement de lexiques sémantiques approvisionnés par les foules : le système WISIGOTH appliqué à Wiktionary

International audienceSemantic lexical resources are a mainstay of various NLP applications. However, comprehensive and reliable resources rarely exist or are often not freely available. We discuss in this paper the context of lexical resources building and the problems of evaluation. We present Wiktionary, a freely available and collaboratively built multilingual dictionary and we propose a semi-automatic approach based on random walks for enriching its synonymy network, which uses endogenous and exogenous data. We then propose a validation "by crowds". Finally, we present an implementation of this system called WISIGOTH.Bien que de nombreuses applications de TAL reposent sur des ressources lexicales sémantiques, celles-ci sont rarement simultanément de qualité satisfaisante et librement disponibles. Partant de la confrontation entre méthodes traditionnelles et tendances émergentes de construction et d'évaluation de ressources lexicales, nous présentons dans cet article une nouvelle méthode fondée sur Wiktionary, un dictionnaire multilingue libre, disponible en ligne et construit collaborativement, puis nous proposons un enrichissement semi-automatique de son réseau de synonymie utilisant des données endogènes et exogènes, recourant à une validation " par les foules ". Nous décrivons enfin une implémentation de ce système baptisée WISIGOTH

SLAM : Solutions lexicales automatique pour métaphores

30 pagesInternational audienceThis article presents SLAM, an Automatic Solver for Lexical Metaphors like “déshabiller* une pomme” (to undress* an apple). SLAM calculates a conventional solution for these productions. To carry on it, SLAM has to intersect the paradigmatic axis of the metaphorical verb “déshabiller*”, where “peler” (“to peel”) comes closer, with a syntagmatic axis that comes from a corpus where “peler une pomme” (to peel an apple) is semantically and syntactically regular. We test this model on DicoSyn, which is a “small world” network of synonyms, to compute the paradigmatic axis and on Frantext.20, a French corpus, to compute the syntagmatic axis. Further, we evaluate the model with a sample of an experimental corpus of the database of Flexse

Invariants and variability of synonymy networks: Self mediated agreement by confluence

International audienceEdges of graphs that model real data can beseen as judgements whether pairs of objectsare in relation with each other or not. So,one can evaluate the similarity of two graphswith a measure of agreement between judgesclassifying pairs of vertices into two cate-gories (connected or not connected). Whenapplied to synonymy networks, such measuresdemonstrate a surprisingly low agreement be-tween various resources of the same language.This seems to suggest that the judgementson synonymy of lexemes of the same lexi-con radically differ from one dictionary ed-itor to another. In fact, even a strong dis-agreement between edges does not necessarilymean that graphs model a completely differ-ent reality: although their edges seem to dis-agree, synonymy resources may, at a coarsergrain level, outline similar semantics. To in-vestigate this hypothesis, we relied on sharedcommon properties of real world data net-works to look at the graphs at a more globallevel by using random walks. They enabledus to reveal a much better agreement betweendense zones than between edges of synonymygraphs. These results suggest that althoughsynonymy resources may disagree at the levelof judgements on single pairs of words, theymay nevertheless convey an essentially simi-lar semantic information