Titlebook: Objects and Databases; International Sympos Klaus Dittrich,Giovanna Guerrini,M.Elena Rodriguez Conference proceedings 2001 Springer-Verlag

Osteopenia

書目名稱Objects and Databases影響因子(影響力)




書目名稱Objects and Databases影響因子(影響力)學科排名




書目名稱Objects and Databases網絡公開度




書目名稱Objects and Databases網絡公開度學科排名




書目名稱Objects and Databases被引頻次




書目名稱Objects and Databases被引頻次學科排名




書目名稱Objects and Databases年度引用




書目名稱Objects and Databases年度引用學科排名




書目名稱Objects and Databases讀者反饋




書目名稱Objects and Databases讀者反饋學科排名

說明

acquisition

DAFT

conifer

Dynamic Clustering in Object-Oriented Databases: An Advocacy for Simplicityhensive usage statistics and the inter-object reference graph. They are quite elaborate. However, they are also complex to implement and induce a high overhead. The third clustering technique, called . (DRO), is based on the same principles, but is much simpler to implement. These three clustering a

煤渣

Opportunistic Prioritised Clustering Framework (OPCF) for object oriented database management systems. The bulk of the work in the area has been on static clustering algorithms which re-cluster the object base when the database is static. However, this type of re-clustering cannot be used when 24-hour database access is required. In such situations .

得罪人

BRAVE

Optimizing Performance of Schema Evolution Sequencesems to the newer OODB systems, the generation of structured web pages from data in database systems, or the integration of systems with different native data models. Such schema transformations are typically composed of a sequence of schema evolution operations. The execution of such sequences can b

繼承人

ODMQL: Object Data Mining Query Languaged systems lead to the demand of a powerful data mining query language. The concepts of such a language for relational databases are discussed before. With the increasing popularity of object-oriented databases, it is important to design a data mining query language for such databases. The main objec

基因組

Benefits of an Object-Oriented Multidimensional Data Modelis lacking in semantics, which can be obtained by using the O-O paradigm. Some benefits that could be obtained by doing this are classified in six O-O-Dimensions (i.e. Classification/Ins- tantiation, Generalization/Specialization, Aggregation/De-composition, Behavioural, Derivability, and Dynamicity