Data Mining-based Fragmentation of XML Data Warehouses

Details Data Mining-based Fragmentation of XML Data Warehouses Data Mining-based Fragmentation of XML Data Warehouses

2008-11-05

arxiv.org/abs/0811.0741v1

ACM 11th International Workshop on Data Warehousing and OLAP (CIKM/DOLAP 08), Napa Valley : \'Etats-Unis d'Am\'erique (2008)

Computer Science

Databases

Scientific paper

With the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data warehouses fail to achieve. However, XML-native database systems currently suffer from limited performances, both in terms of manageable data volume and response time. Fragmentation helps address both these issues. Derived horizontal fragmentation is typically used in relational data warehouses and can definitely be adapted to the XML context. However, the number of fragments produced by classical algorithms is difficult to control. In this paper, we propose the use of a k-means-based fragmentation approach that allows to master the number of fragments through its $k$ parameter. We experimentally compare its efficiency to classical derived horizontal fragmentation algorithms adapted to XML data warehouses and show its superiority.

Affiliated with

Also associated with

No associations

Rating

Data Mining-based Fragmentation of XML Data Warehouses does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Data Mining-based Fragmentation of XML Data Warehouses, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Data Mining-based Fragmentation of XML Data Warehouses will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-373675