Pipelined XPath Query Based on Cost Optimization

XPath query is the key part of XML data processing, and its performance is usually critical for XML applications. In the process of XPath query, there is inherent seriality between query steps, which makes it difficult to parallelize the query effectively as a whole. On the other hand, although XPath query has the characteristics of data stream processing and is suitable for pipeline processing, the data flow of each query step usually varies a lot, which results in limited performance under multithreading conditions. In this paper, we propose a pipelined XPath query method (PXQ) based on cost optimization. This method uses pipelined query primitives to process query steps based on relation index. During pipeline construction, a cost estimation model based on XML statistics is proposed to estimate the cost of the query primitive and provide guidance for the creation of a pipeline phase through the partition of query primitive sequence. The pipeline construction technique makes full use of available worker threads and optimizes the load balance between pipeline stages. The experimental results show that our method can adapt to the multithreaded environment and stream processing scenarios of XPath query, and its performance is better than the existing typical query methods based on data parallelism.

Elements of XPath-like languages in problems of constructing semantic XML models of natural language texts

The subject of the research is the possibility of using XPath-like micro-languages of programming in the generation systems of programs of the PGEN ++ class for the selection and completion of XML-models describing the plan for solving the original problem, according to which the solver program is generated. It is supposed to build such models according to the description of the problem in natural language, thus, we are talking about elements of artificial intelligence technologies. XPath-like language works in the layer of regular-logical expressions (highlighting elements of the primary XML document), performing primary processing of the data obtained in the layer of grammatical parsing of the source text. In addition, XPath-like elements are used to render the final XML models. The standard natural language parsing libraries are used. Non-standard XPath query language extensions are used. For the first time, the idea of expanding the XPath query language to the level of an algorithmic language by introducing the minimum required number of syntactic elements is proposed. It is also proposed to use syntactic elements with an XPath-like structure as both generating and controlling weak constraints of the process of direct inference of final semantic XML models.

Development of a Query Language for GML based on XPath

Geography Markup Language (GML) has been established as the standard language for the transport, storage and modelling of geographic information. In this paper we study how to adapt the XPath query language to GML documents. With this aim, we have defined a semantic based XPath language which is not based on the (tree-based) syntactic structure of GML documents, rather than, it is based on the “semantic structure” of GML documents. In order words, the proposed XPath language is based on the GML schema instead of the syntactic structure. We have developed a system called UALGIS, in order to implement the approach. Such system stores GML documents by means of the PostGIS RDBMS. In order to execute semantic-based XPath queries we have defined a translation of the queries into SQL. Such translation takes into account the GML schema. Finally, the system allows to visualize the result. With this aim, the results of a queries are exported to the Keyhole Markup Language (KML) format.

Retrieving information chunks from a repository of documents SIT Collected from heterogeneous sources

XML documents are generated from heterogeneous resources. They may share the same data but in different Schema, which make it difficult to retrieve information from them. In this paper we propose a new technique that first; minimizes the size of the XML documents by reducing the redundancy of the structure part and generate the repository for these documents, and second; relaxes and decomposes the XPath query in two stages to determine the relevant documents and the relevant part within these documents. The results show significant precision and recall comparing with the exact XPath queries.

A Structural XPath Query Expansion Approach Based on XML Schema in Publish Subscribe System

XML based publish/subscribe systems are on tremendous rise during recent years. In order to get interested documents, the subscribers submit an XPath Query. In such applications, there is often a mismatch between how publishers describe entities and how different subscribers express their interests. Lots of researches focus on filtering mechanisms, exists such as XFilter, YFilter, Afilter etc, but most of these mechanisms do not use the structural property of XML. This paper proposes an approach which dose XPath query expansion based on structural information. Firstly check query node in OWL classes and return semantically related data performing semantic normalized. Secondly, perform structural expansion depend on the XSD which set constraint on content published. Experiment results show that our approach performs well across a range of XPath queries and documents.