• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.673-682
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• 2009

XML data are widely used for data representation and exchange on the Web and the data type is an continuous stream in ubiquitous environment. Therefore there are some mining researches related to the extracting of frequent structures and the efficient query processing of XML stream data. In this paper, we propose a mining method to extract frequent structures of XML stream data in recent window based on the sliding window. XML stream data are modeled as a tree set, called XFP_tree and we quickly extract the frequent structures over recent XML data in the XFP_tree.

• Journal of Information Technology Applications and Management
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• v.16 no.4
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• pp.245-261
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• 2009

Since XML emerged as a standard for data exchange on the web, it has been widely used for applications like e-Commerce, CRM, and BI. However, it is common that most of business data is stored in relational database systems, and it is expected that business data management would still be centered around the relational database systems. As such, the technique of viewing relational data as XML and processing XML queries against it is required. To meet such a need, in the SQL/XML standard, the functions to publish relational data as XML are provided. In this paper, we propose the techniques of providing an XML view of relational data defined by an SQL/XML statement in DTD(Document Type Definition), and of processing XPath queries against the XML view by translating them into SQL/XML statements, and describe the validation of such techniques through implementation and tests.

• The Journal of Society for e-Business Studies
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• v.8 no.1
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• pp.103-111
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• 2003

Nowadays XML is used for exchanging information in e-Commerce, especially B2B. Necessity of XML DBMS has being increased to efficiently process XML data. So a lots of database products for supporting XML are rapidly appeared in the market. In this paper, we made an XML DBMS system based on Generic Data Model. First we developed XML Adaptor based on Generic Data Model and added it on relational DBMS for developing XML DBMS. XML Adaptor is composed of Query Convertor and XML Repository System. The Query Convertor parse commands that are for XML data manipulation and then call the relevant component of XML Repository System for relational database operation. The XML Repository System handles relational database operations such as create, delete, store, and etc. In this way we can use a relational DBMS for manipulation XML data. Therefor we can build more economically XML DBMS.

• Journal of KIISE:Databases
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• v.34 no.3
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• pp.270-281
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• 2007

Recently, there has been growing interest in streaming XML data. Much of the work on streaming XML data has been focused on efficient filtering of XML data. Such XML filtering systems deliver XML documents to interested users. The burden of extracting the XML fragments of interest from XML documents is placed on users. As a result, several evaluation techniques for streaming XML data, which only extract interested XML fragments by directly evaluating XML queries on streaming XML data, have been proposed. However, existing evaluation techniques for streaming XML data only support the restricted subset of XPath queries, and multiple queries cannot be evaluated by such evaluation techniques. In this paper, we propose XTREAM which evaluates multiple queries in conjunction with the read-once nature of streaming data. In contrast to the previous work, XTREAM supports a wide class of XPath queries including order based predicates and so on. Experimental results with real-life and synthetic XML data demonstrate the efficiency and scalability of XTREAM.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.199-210
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• 2005

We need XML generate various kinds of XML data to evaluate XML database systems. Existing XML data generators are developed to generate XML data that are suitable for particular evaluation methods, and their functionalities are limited in terms of generating XML data This paper introduces a new XML data generator, WeXGene, that not only improves the drawbacks of existing data generators but also adds new data generation functionalities. For generating XML data WeXGene uses the user data files and the structure definition files, which specify SDTD(Symbolic DTD) or input parameters. The user data file is a text data file that has column data or row data. It is also possible that WeXGene generates XML data without accessing the user data file. This paper presents the design details, overall system architecture, and data generation process of WeXGene. An analytic comparison with other XML data generators is also presented.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.441-451
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• 2005

HTML is mostly stored in native file systems instead of specialized repositories such as a database. Like HTML, XML, the standard for the exchange and the representation of data in the Internet, is mostly resident on native file systems. However. since XML data is irregular and verbose, the disk space and the network bandwidth are wasted compared to those of regularly structured data. To overcome this inefficiency of XML data, the research on the compression of XML data has been conducted. Among recently proposed XML compression techniques, some techniques do not support querying compressed data, while other techniques which support querying compressed data blindly encode data values using predefined encoding methods without considering the types of data values which necessitates partial decompression for processing range queries. As a result, the query performance on compressed XML data is degraded. Thus, this research proposes an XML compression technique which supports direct and efficient evaluations of queries on compressed XML data. This XML compression technique adopts an encoding method, called dictionary encoding, to encode each tag of XML data and applies proper encoding methods for encoding data values according to the inferred types of data values. Also, through the implementation and the performance evaluation of the XML compression technique proposed in this research, it is shown that the implemented XML compressor efficiently compresses real-life XML data lets and achieves significant improvements on query performance for compressed XML data.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.23-30
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• 2008

The basic research of context aware in ubiquitous environment is an internet technique and XML. The XML data of continuous stream type are popular in network application through the internet. And also there are researches related to query processing for streaming XML data. As a basic research to efficiently query, we propose not only a labeled ordered tree model representing the XML but also a mining method to extract frequent structures from streaming XML data. That is, XML data to continuously be input are modeled by a stream tree which is called by XFP_tree and we exactly extract the frequent structures from the XFP_tree of current window to mine recent data. The proposed method can be applied to the basis of the query processing and index method for XML stream data.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.27-37
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• 2004

XML has been proposed as a document standard for the representation and exchange of data on the WWW, and also becoming a standard for the search and reuse of scattered documents. When implementing a XML contents management system, special consideration should be imposed on how to model data and how to store the modelled data for effective and efficient management of the semi-structured data. In this paper, we proposed a new data model for the storage and search of XML document data. This proposed data model could represent both of data and structure views of XML documents, and be applied to the new data system for XML documents as well as the existing data systems.

• Proceedings of the Korea Association of Information Systems Conference
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• 2005.05a
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• pp.65-78
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• 2005

Nowadays, large amounts of XML documents are available on the Internet. Thus, we need to analyze them multi-dimensionally in the same way as relational data. In this paper, we propose a new frame-work for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where every fact data as well as dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new multidimensional expression language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate the measure data. They specify text mining operators for aggregating text constituting the measure data. We evaluate XML-OLAP by applying it to a U.S. patent XML warehouse. We use XML-MDX queries, which demonstrate that XML-OLAP is effective for multi-dimensionally analyzing the U.S. patents.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.94-100
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• 2006

Computing paradigm shift to internet-based one has accelerated the use of XML in diverse applications. This phenomena has made the explosive increases of XML data and it triggered many active researches in maintaining very huge amount of XML data in turn. In this paper we present a persistent graph-based XML indexing lot data-centric XML data. In our approach we use 3 graphs to represent XML indexes and XML data itself. They are schema graph, data graph index. And then we have mapped those graphs to B+-trees the persistency. With our approach we can achieve linear query execution time with the increase of XML sizes.