• Journal of KIISE:Databases
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• v.31 no.3
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• pp.307-319
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• 2004

Recently, ebXML and Web Services are emerging as the XML-based electronic business frameworks. To provide a set of registry services which users or applications can store and search the business information, ebXML and Web Services use ebXML registry and UDDI registry, respectively. They use the different registries each other, but there are something that similiar to the structure and functions of both of registries. In this paper, we analyze the similarity of ebXML Registry Information Model(RIM) and UDDI data structure, and construct the mapping information. So, we design and implement the UDDI Service Middleware which translates the request of UDDI registry service into the request of ebXML registry service using the algorithm. Consequently, we could use the ebXML registry like ebXML registry as well as UDDI registry without any changes in the ebXML registry itself so that we can not need to have both of registries for e-business.

• 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 KIISE:Databases
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• v.32 no.6
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• pp.641-649
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• 2005

As XML is widely used with the development of internet, many researches on the XML storage and query processing have been done Several index techniques have been proposed to efficiently process XML path queries. Recently, structural join has received murk attention as a method to protest the path query. Structural join technique process a path query by identifying the containment relationship of elements. Especially, it has an advantage that we can get the result set by simply comparing related elements only instead of scanning whole document. However during the comparison process, unnecessary elements that are not included in the result set can be scanned. So we propose a new technique, the level structural join. In this technique, we use both the relationship and the level distribution of elements in the path query. Using this technique, we tao improve the performance of query processing only by comparing elements with specific level in the target inverted level.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.317-324
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• 2006

In this paper, we propose a new indexing technique to solve various queries which have a strong good point not only database indexing schema take advantage of converting from semi-structured data to structured data but also performance is more faster than before. We represent structure information of XML document between nodes of tree that additional numbering information which can be bit-stream without modified structure of XML tree. And, We add in indexing schema searching incidental structure information in the process. In Querying schema, we recover ancestor nodes through give information of node using indexing schema in complete path query expression as well as relative path query expression. Therefore, it takes advantage of making derivative query expression with given query. In this process, we recognize that indexing and querying schema can get searched result set faster and more accurate. Because response time is become shorter by bit operating, when query occur and it just needs information of record set earch node in database.

• Journal of Computing Science and Engineering
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• v.6 no.2
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• pp.127-140
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• 2012

In this paper, we focus on efficient construction of tightest matched subtree (TMSubtree) results, for keyword queries on extensible markup language (XML) data, based on smallest lowest common ancestor (SLCA) semantics. Here, "matched" means that all nodes in a returned subtree satisfy the constraint that the set of distinct keywords of the subtree rooted at each node is not subsumed by that of any of its sibling nodes, while "tightest" means that no two subtrees rooted at two sibling nodes can contain the same set of keywords. Assume that d is the depth of a given TMSubtree, m is the number of keywords of a given query Q. We proved that if d ${\leq}$ m, a matched subtree result has at most 2m! nodes; otherwise, the size of a matched subtree result is bounded by (d - m + 2)m!. Based on this theoretical result, we propose a pipelined algorithm to construct TMSubtree results without rescanning all node labels. Experiments verify the benefits of our algorithm in aiding keyword search over XML data.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.5-12
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• 2004

The data transformation between XML and Relation Database is made through the Principle of mapping bewtween them. There are two ways to access SQL Server, one is to assign SQL query to URL and the other is to use template file. MS-SQL server takes advantage of OpenXML function to transform the results of executing SQL query into XML documents. That is, OpenXML first makes node tree and then transforms row set data of XML documents into XML data of relation type. In order to insert XML data into database data. data is extracted from parsing XML documents using sp_xml_preparedocument procedure, and then the document structure is mapped into tree structure and stored in a table of database. Consequently, Data transformation between XML and Relation Database is made through mapping bewtween them. This article proposes the principle of mapping between XML and Relation Database and then shows the implementation of transformation between them so that it introduces the possibilty of bringing the extension and efficiency of data and various effects.

• Journal of KIISE:Databases
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• v.33 no.5
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• pp.513-525
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• 2006

Search results of XML keyword search are defined generally as the most specific elements containing all query keywords in the literature. The labels of XML elements and semantic information such as ontology, conceptual model, thesaurus, and so on, are used to improve the preciseness of the search results. This paper presents a hierarchical index for an efficient XML keyword query processing on the condition that returnable search concepts are defined and users' query concepts can be interpreted with the help of the semantic information. The hierarchical index separately stores the XML elements containing a keyword on the basis of the hierarchical relations of the concepts that the XML elements belong to, and makes it possible to obtain least common ancestors, which are candidates for the search results, with selectively reading the elements belonging to the concepts relevant to query concepts and without considering all the combinations of the elements having been read. This paper deals with how to organize the hierarchical index and how to process XML keyword queries with the index. In our experiment with the DBLP XML document and the XML documents in the INEX2003 test set, the hierarchical index worked well.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.118-126
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• 2003

In data mining, having access to large amount of data sets for the purpose of predictive data does not guarantee good method, even where the size of Real data is Mobile commerce unlimited. In addition to searching expected Goods objects for Users, it becomes necessary to develop a recommendation service based on XML. In this paper, we design the optimized XML Recommender product data. Efficient XML data preprocessing is required, include of formatting, structural, and attribute representation with dependent on User Profile Information. Our goal is to find a relationship among user interested products from E-Commerce and M-Commerce to XDB. Firstly, analyzing user profiles information. In the result creating clusters with analyzed user profile such as with set of sex, age, job. Secondly, it is clustering XML data which are associative products classify from user profile in shopping mall. Thirdly, after composing categories and goods data in which associative objects exist from the first clustering, it represent categories and goods in shopping mall and optimized clustering XML data which are personalized products. The proposed personalized user profile clustering method has been designed and simulated to demonstrate it's efficient.

• The Journal of the Convergence on Culture Technology
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• v.3 no.1
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• pp.19-23
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• 2017

With the increase in the number of smart phone users, smart phones themselves are seeing progress in terms of available functions. Many applications, too, are being developed to increase convenience in daily life. This study issued a list of information on films that the user wishes to see, by using an XML parser to call news articles related to the films in question to the news site RSS. The Android App server was built using Ubuntu and the latest film information was provided through the board that was built. The menu was consisted in a manner so that when the information interested was clicked on, a more detailed set of information became available.

• Journal of KIISE:Software and Applications
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• v.29 no.9
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• pp.676-683
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• 2002

The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.