RQL : un langage " à la SQL " pour découvrir des règles à partir des données

National audienceRQL (pour Rule Query Language) est un langage de requêtes " à la SQL " qui étend et généralise les dépendances fonctionnelles 1 à de nouvelles catégories de règles. RQL apporte aux analystes de données un outil pratique pour découvrir les implications logiques entre attributs d'une base de données. Ces implications peuvent mettre en évidence des problèmes de qualité de données ou de nouvelles corrélations inattendues entre les attributs. Le traitement de ces requêtes RQL est basé sur une technique de réécriture qui délègue un maximum de calculs au SGBD sous-jacent. Cette contribution vise à renforcer le lien entre la fouille de données et les bases de données et de faciliter l'utilisation de techniques de fouille par des analystes ou des étudiants habitués au SQL

Helium implanted gallium nitride evidence of gas-filled rod-shaped cavity formation along the c-axis

structural defects induced by He implantation in GaN epilayer at high fluence (1 X 10(17) He/cm(2)) and elevated temperature (750 degrees C) have been studied by conventional and high resolution transmission electron microscopy. In addition to the planar interstitial-type defects lying in the basal plane usually observed after high fluence implantation into GaN, a continuous layer of bubbles arranged in rows parallel to the implanted surface is observed in the region of maximum He concentration. This arrangement of bubbles is ascribed to interactions with dislocations. Beyond, one dimensional rod-shaped defects appear perpendicular to the implanted surface. Contrast analysis of high resolution images and atomistic simulations gives converging results in the determination of the nature and structure of these defects, i.e., gas-filled rod-shaped cavities in an overpressurized state. (c) 2008 American Institute of Physics

Reduced Heterochromatin Formation on the pFAR4 Miniplasmid Allows Sustained Transgene Expression in the Mouse Liver

International audienceNon-viral gene delivery into the liver generally mediates a transient transgene expression. A comparative analysis was performed using two gene vectors, pFAR4 and pKAR4, which differ by the absence or presence of an antibiotic resistance marker, respectively. Both plasmids carried the same eukaryotic expression cassette composed of a sulfamidase (Sgsh) cDNA expressed from the human alpha antitrypsin liver-specific promoter. Hydrodynamic injection of the pFAR4 construct resulted in prolonged sulfamidase secretion from the liver, whereas delivery of the pKAR4 construct led to a sharp decrease in circulating enzyme. After induction of hepatocyte division, a rapid decline of sulfamidase expression occurred, indicating that the pFAR4 derivative was mostly episomal. Quantification analyses revealed that both plasmids were present at similar copy numbers, whereas Sgsh transcript levels remained high only in mice infused with the pFAR4 construct. Using a chromatin immunoprecipitation assay, it was established that the 5' end of the expression cassette carried by pKAR4 exhibited a 7.9-fold higher heterochromatin-to-euchromatin ratio than the pFAR4 construct, whereas a bisulfite treatment did not highlight any obvious differences in the methylation status of the two plasmids. Thus, by preventing transgene expression silencing, the pFAR4 gene vector allows a sustained transgene product secretion from the liver

RQL: An SQL-like Query Language for Discovering Meaningful Rules (demo)

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RQL: A Query Language for Rule Discovery in Databases

International audiencePromoting declarative approaches in data mining is a long standing theme, the main idea being to simplify as much as possible the way data analysts interact with their data. This paper goes into this direction by proposing a well-founded logical query language, Saf eRL, allowing the expression of a wide variety of rules to be discovered against a database. By rules, we mean statements of the form " if. .. then. .. " , as defined in logics for " implications " between boolean variables. As a consequence, Saf eRL extends and generalizes functional dependencies to new and unexpected rules. We provide a query rewriting technique and a constructive proof of the main query equivalence theorem, leading to an efficient query processing technique. From Saf eRL, we have devised RQL, a user-friendly SQL-like query language. We have shown how a tight integration can be performed on top of any relational database management system. Every RQL query turns out to be seen as a query processing problem, instead of a particular rule mining problem. This approach has been implemented and experimented on sensor network data. A web prototype has been released and is freely available (http://rql.insa-lyon.fr). Data analysts can upload a sample of their data, write their own RQL queries and get answers to know whether or not a rule holds (if not, a counter example from the database is displayed) and much more

Query Rewriting for Rule Mining in Databases

International audiencePromoting declarative approaches in data mining is a long standing theme. This paper goes into this direction by proposing a well- founded logical query language, SafeRL, allowing the expression of a wide variety of “rules” to be discovered against the data. SafeRL ex- tends and generalizes functional dependencies in databases to new and unexpected rules easily expressed with a SQL-like language. In this set- ting, every rule mining problem turns out to be seen as a query process- ing problem. We provide a query rewriting technique and a construc- tive proof of the main query equivalence theorem, leading to an efficient query processing technique. Based on a concrete SQL-like grammar for SafeRL, we show how a tight integration can be performed on top of any DBMS. The approach has been implemented and experimented on sensor network data. This contribution is an attempt to bridge the gap between pattern mining and databases and facilitates the use of data mining techniques by SQL-aware analysts

Query Rewriting for Rule Mining in Databases

International audiencePromoting declarative approaches in data mining is a long standing theme. This paper goes into this direction by proposing a well- founded logical query language, SafeRL, allowing the expression of a wide variety of “rules” to be discovered against the data. SafeRL ex- tends and generalizes functional dependencies in databases to new and unexpected rules easily expressed with a SQL-like language. In this set- ting, every rule mining problem turns out to be seen as a query process- ing problem. We provide a query rewriting technique and a construc- tive proof of the main query equivalence theorem, leading to an efficient query processing technique. Based on a concrete SQL-like grammar for SafeRL, we show how a tight integration can be performed on top of any DBMS. The approach has been implemented and experimented on sensor network data. This contribution is an attempt to bridge the gap between pattern mining and databases and facilitates the use of data mining techniques by SQL-aware analysts

Une Approche d'Extraction de Motifs Graduels (Fermés) Fréquents Sous Contrainte de la Temporalité

International audienceLa fouille de motifs graduels a pour but la découverte de co-variations fréquentes entre attributs numériques dans une base de données. Plusieurs algorithmes d'extraction automatique de tels motifs ont été proposés. La principale différence entre ces algorithmes réside dans la sémantique de variation considérée. Dans certains domaines d'application, on trouve des bases de données dont les objets sont munis d'une relation d'ordre temporel. Ainsi, du fait de leur sémantique de variation, les algorithmes de la littérature sont inadaptés pour de telles données. Dans ce contexte, nous proposons une approche de fouille de motifs graduels sous contrainte d'ordre temporel, qui réduit le nombre de motifs générés. Une étude expérimentale sur des bases de données paléoécologiques permet d'apprendre les groupements d'indicateurs qui modélisent l'évolution de la biodiversité. Les connaissances apportées par ces groupements montrent l'intérêt de notre approche pour le domaine environnemental