Interactive Join Query Inference with JIM

Bonifati, Angela; Ciucanu, Radu; Staworko, Slawomir

Document type :

Communication dans un congrès avec actes

Title :

Interactive Join Query Inference with JIM

Author(s) :

Bonifati, Angela [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Linking Dynamic Data [LINKS]
Ciucanu, Radu [Auteur correspondant]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Linking Dynamic Data [LINKS]
Staworko, Slawomir [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Linking Dynamic Data [LINKS]

Conference title :

Gestion de Données - Principes, Technologies et Applications (BDA)

City :

Grenoble-Autrans

Country :

France

Start date of the conference :

2014-10-14

HAL domain(s) :

Informatique [cs]/Base de données [cs.DB]

English abstract : [en]

Specifying join predicates may become a cumbersome task in many situations e.g., when the relations to be joined come from disparate data sources, when the values of the attributes carry little or no knowledge of metadata, ...
Show more >Specifying join predicates may become a cumbersome task in many situations e.g., when the relations to be joined come from disparate data sources, when the values of the attributes carry little or no knowledge of metadata, or simply when the user is unfamiliar with querying formalisms. Such task is recurrent in many traditional data management applications, such as data integration, constraint inference, and database denormalization, but it is also becoming pivotal in novel crowdsourcing applications. We present Jim (Join Inference Machine), a system for interactive join specification tasks, where the user infers an n-ary join predicate by selecting tuples that are part of the join result via Boolean membership queries. The user can label tuples as positive or negative, while the system allows to identify and gray out the uninformative tuples i.e., those that do not add any information to the final learning goal. The tool also guides the user to reach her join inference goal with a minimal number of interactions.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Nationale

Popular science :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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Interactive Join Query Inference with JIM

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