A comprehensive guide through the Italian database research over the last 25 years

• 其他作者：
  • Flesca, Sergio, editor.
  • Greco, Sergio, editor.
  • Masciari, Elio, editor.
  • Sacca, Domenico, editor.
  • SpringerLink (Online service)
• 其他題名：
  • Studies in big data ;
• 出版： Cham : Springer International Publishing :Imprint: Springer
• 叢書名： Studies in big data,volume 31
• 主題： Databases--Research. , Engineering. , Computational Intelligence. , Big Data. , Artificial Intelligence (incl. Robotics) , Big Data/Analytics. , Data Mining and Knowledge Discovery.
• ISBN： 9783319618937 (electronic bk.) 、 9783319618920 (paper)
• FIND@SFXID: CGU
• 資料類型: 電子書
• 內容註: The visual side of the data -- Digital Libraries: From Digital Resources to Challenges in Scientific Data Sharing and Re-use -- From Data Integration to Big Data Integration -- Matching Techniques for Data Integration and Exploration: from Databases to Big Data -- 25+ Years of Query Processing - From a Single, Stored Data Set to Big Data -- From Star Schemas to Big Data: 20+ Years of Data Warehouse Research -- A short account of techniques for assisting users in mastering Big Data -- Multimedia, Similarity, and Preferences: Adding Flexibility to Your Information Needs -- Dealing with Inconsistency in Databases: An Overview -- First-order Ontology Mediated Database Querying via Query Reformulation -- Using ontologies for semantic data integration -- Schema Mappings: from Data Translation to Data Cleaning.
• More
• 摘要註: This book offers readers a comprehensive guide to the evolution of the database field from its earliest stages up to the present--and from classical relational database management systems to the current Big Data metaphor. In particular, it gathers the most significant research from the Italian database community that had relevant intersections with international projects. Big Data technology is currently dominating both the market and research. The book provides readers with a broad overview of key research efforts in modelling, querying and analysing data, which, over the last few decades, have became massive and heterogeneous areas.
• 讀者標籤：

  需登入
• 引用連結：

  Copy Link
• 目前引用數
• Share: