Group items tagged

Google Image Swirl organizes image search results into groups and sub-groups, based on their visual and semantic similarity and presents them in an intuitive exploratory interface.

"Présentation graphique des pages (ressemble à un groupe de post-it ou des images "pinnées" sur un babillard)"

Signets de Sylvie Dalbin autour des moteurs de recherche. Voir aussi les tags : moteur-de-recherche(exemple) recherche recherche-contenu-illustration(sujet) recherche-contenu-image(sujet) recherche-contenu(sujet) recherche-développement(nature_info) recherche-facette(exemple) recherche-facette(sujet) recherche-fédérée(exemple) recherche-fédérée(sujet) recherche-filtre(sujet) recherche-information(exemple) recherche-information(sujet) recherche-multilingue(sujet) recherche-par-graphe(sujet) recherche-personnalisable(sujet) recherche-question-reponse(sujet) recherche-tri(sujet) recherche(domaine) recherche(sujet)

"Abrégée en RI ou IR (Information Retrieval en anglais), la recherche d'information est la science qui consiste à rechercher l'information dans des documents - les documents eux-mêmes ou les métadonnées qui décrivent les documents -, dans des bases de données - qu'elles soient relationnelles ou mises en réseau par des liens hypertexte comme dans le World Wide Web, l'internet, et les intranets, pour le texte, le son, les images, les données."

Feature Highlights : - Leoad Data Easily - Filter and Navigate - Group Data in Tables - Display on the Web * 100% java technology. * A range of different relationship types are supported. Edges can be directed, undirected, and can show flow in both directions. * Text and numerical attributes can be associated with nodes and edges. Tables display the attributes and allow sorting. * Images can be associated with nodes. * Advanced cluster computation reveals inherent groupings. * Co-citations and co-occurrence analysis clarifies dense networks.

A sandbox for collecting search examples, patterns, and anti-patterns. Using our group pool (http://www.flickr.com/groups/searchpatterns/), you can also talk about search and discovery; and even add new examples and patterns.

"The University of Calgary's Libraries and Cultural Resources became a beta partner with Serials Solutions' unified discovery service, Summon, in the spring of 2009. Since then it has worked to include metadata from numerous disparate systems in a single index to drive discovery in a Google-like environment. The University of Calgary has examined how MARC and other metadata schemas are mapped into Summon with an eye to ensuring the maximum possible population of index fields representing facets in addition to adhering to the established standards for cross mapping metadata schemas and indexing. The University of Calgary has investigated existing standards and worked closely with the Summon team to create mappings that reflect how MARC and other metadata can ultimately be used in big indexes. Combined with the normalization or collapsing of metadata records representing the same resource into a single metadata-rich record, fully leveraging MARC and other metadata in big indexes should not only level the metadata playing field but make competition between records a non-issue."