XWeB: the XML Warehouse Benchmark

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of benchmarks. However, decision support benchmarks do not currently support XML features. In this paper, we introduce the XML Warehouse Benchmark (XWeB), which aims at filling this gap. XWeB derives from the relational decision support benchmark TPC-H. It is mainly composed of a test data warehouse that is based on a unified reference model for XML warehouses and that features XML-specific structures, and its associate XQuery decision support workload. XWeB's usage is illustrated by experiments on several XML database management systems

Improvements in or relating to inhibition of corrosion by natural waters in cooling systems

This paper presents an approach for ranking semantic Web service advertisements with respect to a service request. The use of recall and precision is proposed as suitable measures for determining the degree of match between the request and the advertisement. Ranking is based on the use of the domain ontology to infer the semantic similarity between the parameters of the request and the advertisement. The proposed approach is applicable to several types of ontologies, ranging from simple taxonomies to highly expressive ontologies, such as OWL ontologies

Australian swimmer Miss Kitty Mackay, New South Wales, 7 March 1932 [picture].

Title devised from accompanying information where available.; Part of the: Fairfax archive of glass plate negatives.; Fairfax number: 3415.; Also available online at: http://nla.gov.au/nla.pic-vn6219999; Acquired from Fairfax Media, 2012

Pattern-based query answering

Users without knowledge of schemas or structured query languages have difficulties in accessing information stored in databases. Commercial and research efforts have focused on keyword-based searches. Among them, precis queries generate entire multi-relation databases, which are logical subsets of existing ones, instead of individual relations. A logical database subset contains not only items directly related to the query selections but also items implicitly related to them in various ways. Existing approaches to précis query answering assume that a database is pre-annotated with a set of weights, and when a query is issued, an ad-hoc logical subset is constructed on the fly. This approach has several limitations, such as dependence on users for providing appropriate weights and constraints for answering précis queries, and difficulty to capture different query semantics and user preferences. In this paper, we propose a pattern-based approach to logical database subset generation, Patterns of logical subsets corresponding to different queries or user preferences may be recognized and stored in the system. Each time a user poses a question, the system searches in a repository of précis patterns to extract an appropriate one. Then, this is enriched with tuples extracted from the database, in order to produce the logical database subset. © Springer-Verlag Berlin Heidelberg 2006