A Framework for Automatically Interpreting Tabular Data at Orange
Résumé
Large parts of knowledge of companies are encoded in tabular data. Being able to interpret such data is key to increase business efficiency and to propose innovative services, and Orange is no exception. With more than 140,000 employees worldwide and a heterogeneous client portfolio, Orange produces a phenomenal amount of tabular data every day. These tables are viscerally embedded in internal services and products (e.g., network logs, multimedia catalogs). Hence, they are a source to discover new knowledge. Although this encourages the development of efficient tools to process them, several issues are negatively impacting their use. First, the volume curse makes difficult to identify the right dataset for a given use case. Then, the knowledge gap between data producers/consumers is exacerbated by our language footprint (seven main languages), the heterogeneous tools producing various table formats, and the experience/jobs of employees leading to similar concepts being expressed by different terms across tables.
Domaines
Informatique [cs]
Origine : Fichiers produits par l'(les) auteur(s)