Compressed materialised views of semi-structured data

Query performance issues over semi-structured data have led to the emergence of materialised XML views as a means of restricting the data structure processed by a query. However preserving the conventional representation of such views remains a significant limiting factor especially in the context of mobile devices where processing power, memory usage and bandwidth are significant factors. To explore the concept of a compressed materialised view, we extend our earlier work on structural XML compression to produce a combination of structural summarisation and data compression techniques. These techniques provide a basis for efficiently dealing with both structural queries and valuebased predicates. We evaluate the effectiveness of such a scheme, presenting results and performance measures that show advantages of using such structures

Optimizing Spatial Databases

This paper describes the best way to improve the optimization of spatial databases: through spatial indexes. The most commune and utilized spatial indexes are R-tree and Quadtree and they are presented, analyzed and compared in this paper. Also there are given a few examples of queries that run in Oracle Spatial and are being supported by an R-tree spatial index. Spatial databases offer special features that can be very helpful when needing to represent such data. But in terms of storage and time costs, spatial data can require a lot of resources. This is why optimizing the database is one of the most important aspects when working with large volumes of data.Spatial Database, Spatial Index, R-tree, Quadtree, Optimization

Incremental natural-language processing with schema-tree adjoining grammars

Schema-Tree Adjoining Grammars are proposed for compressing natural-language grammars. Their rules allow for regular expressions associated with inner nodes of elementary trees referring to individual sons of inner nodes in order to describe their occurrences and repetitions in the set of elementary trees specified. In the following, the adequacy of representing a possibly infinite set of trees by one scheme is discussed for incremental natural-language processing where the input is consumed and processed piecemeal. The basic idea is to avoid decisions for which not enough information is available at the moment by the condensed representation of all currently valid alternatives in terms of semi-instantiated schemata. We present an extended Early processing which allows for mixing partially instantiated trees and uninstantiated schemata