• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.680-693
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• 2008

Recent studies on XML filtering assume that all data sources follow a single global schema defined in a filtering system. However, beyond this simple assumption, a filtering system can provide a service that allows data publishers to have their own schema; hence, the data sources will become heterogeneous. The number of data sources is expected to be large in a filtering system and the data sources are frequently published, updated, and disappeared, that is, dynamic. In this paper, we introduce implementing a simple and efficient XPath query translation method for such a dynamic environment. The method is especially targeted for a query which is composed based only on users' knowledge and experience without a graphical guidance of the global schema. When a user queries a large number of heterogeneous data, there is a high possibility that the query is not consistent with the same local schema assumed by the user. Our query translation method also supports a function for this problem. Some experimental results for query translation performance have shown that our method has reasonable performance, and is more practical than the existing method.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.1-10
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• 2006

This paper introduces the development XPERT(XML Query Processing Engine using Relational Technologies) which is based on relational model. In our system we have used a decomposed approach to store XML files in relational tables. XML queries are translated to SQLs according to the table schema, and then they are sent to the relational DBMS to get the results back. Our translation scheme produces AST(Abstract Syntax Tree) by analyzing XQuery expressions at first. And on traversing AST proper SQLs are generated. Translated SQLs can reduce the number of joins by using path information and utilize dewey number to preserve document originated orderings among compoments in XML. In addition we propose the efficient algorithms of XPath and XQuery translation. And finally we show the implementation of our prototype system for the functional evaluations.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.430-433
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• 2007

There have been several researches to manipulate XML Queries efficiently since XML has been accepted in many areas. Among the many of the researches majority of them adopt relational databases as underlying systems because relational model which is used the most widely for managing large data efficiently. In this paper we develop XQuery to SQL Translation Algorithms called XSTAR that can efficiently handle XPath, XQuery FLWORs with nested iteration expressions, element constructors and keywords retrieval on relational database as well as constructing XML fragments from the transformed SQL results. The entire algorithms mentioned in XSTAR have been implemented as the XQuery processor engine in XML management system, XPERT, and we can test and confirm it's prototype from "http ://dblab.kmu.ac.kr/project.jsp".