Benchmarking Summarizability Processing in XML Warehouses with Complex Hierarchies
Chantola Kit (ERIC), Marouane Hachicha (ERIC), J\'er\^ome Darmont, (ERIC)

TL;DR
This paper introduces an extended XML warehouse benchmark with complex hierarchies to evaluate summarizability processing, addressing a gap in existing benchmarks and aiding performance comparison of different solutions.
Contribution
It proposes an extension to the XWeB benchmark to include complex hierarchies, enabling better evaluation of summarizability solutions in XML data warehouses.
Findings
Complex hierarchies can be generated in benchmark datasets.
The extended benchmark allows comparison of summarizability approaches.
Experimental results validate the benchmark's effectiveness.
Abstract
Business Intelligence plays an important role in decision making. Based on data warehouses and Online Analytical Processing, a business intelligence tool can be used to analyze complex data. Still, summarizability issues in data warehouses cause ineffective analyses that may become critical problems to businesses. To settle this issue, many researchers have studied and proposed various solutions, both in relational and XML data warehouses. However, they find difficulty in evaluating the performance of their proposals since the available benchmarks lack complex hierarchies. In order to contribute to summarizability analysis, this paper proposes an extension to the XML warehouse benchmark (XWeB) with complex hierarchies. The benchmark enables us to generate XML data warehouses with scalable complex hierarchies as well as summarizability processing. We experimentally demonstrated that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Database Systems and Queries · Data Mining Algorithms and Applications · Data Management and Algorithms
