When object databases arrived on the scene some ten years ago, they provided database capabilities for previously neglected, complex applications, such as CAD, but were burdened with one inherent teething problem, poor performance. Physical database design is one tool that can provide performance improvements and it is the general area of concern for this thesis. Clustering is one fruitful design technique which can provide improvements in performance. However, clustering in object databases has not been explored in depth and so has not been truly exploited. Further, clustering, although a physical concern, can be determined from the logical model. The object model is richer than previous models, notably the relational model, and so it is a...
[[abstract]]For dynamic clustering of objects, a data accessing model of online object-oriented data...
Many machine-learning (either supervised or unsupervised) techniques assume that data present themse...
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where t...
We investigate clustering techniques that are specifically tailored for object-oriented database sys...
International audienceIt is widely acknowledged that good object clustering is critical to the perfo...
International audienceIt is widely acknowledged that a good object clustering is critical to the per...
The topic of this article is multi-criterion, structure-based clustering in objectoriented databases...
International audienceA good object clustering is critical to the performance of object-oriented dat...
Conventional object-oriented database (OODB) models and systems take a static, classification-based ...
Recent studies on modern database management systems consider object-oriented databases as a possibl...
International audienceWe present in this chapter an overview of the benchmarks aimed at evaluating t...
International audienceWe present in this chapter an overview of the benchmarks aimed at evaluating t...
Clustering becomes an indispensable requirement while dealing with immense volume of data. Since Dat...
grantor: University of TorontoTo achieve high performance on shared memory multiprocessors...
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where t...
[[abstract]]For dynamic clustering of objects, a data accessing model of online object-oriented data...
Many machine-learning (either supervised or unsupervised) techniques assume that data present themse...
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where t...
We investigate clustering techniques that are specifically tailored for object-oriented database sys...
International audienceIt is widely acknowledged that good object clustering is critical to the perfo...
International audienceIt is widely acknowledged that a good object clustering is critical to the per...
The topic of this article is multi-criterion, structure-based clustering in objectoriented databases...
International audienceA good object clustering is critical to the performance of object-oriented dat...
Conventional object-oriented database (OODB) models and systems take a static, classification-based ...
Recent studies on modern database management systems consider object-oriented databases as a possibl...
International audienceWe present in this chapter an overview of the benchmarks aimed at evaluating t...
International audienceWe present in this chapter an overview of the benchmarks aimed at evaluating t...
Clustering becomes an indispensable requirement while dealing with immense volume of data. Since Dat...
grantor: University of TorontoTo achieve high performance on shared memory multiprocessors...
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where t...
[[abstract]]For dynamic clustering of objects, a data accessing model of online object-oriented data...
Many machine-learning (either supervised or unsupervised) techniques assume that data present themse...
This paper describes the incorporation of seven stand-alone clustering programs into S-PLUS, where t...