• 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.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.75-94
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• 2009

Since XML emerged as a standard for data exchange on the web, it has been established as a core component in e-Commerce and efficient query processing over XML data in ubiquitous computing environment has been also receiving much attention. Recently, the techniques were proposed whereby an XML document is fragmented into XML fragments to be streamed and the mobile clients receive the stream while processing queries over it. In processing queries over an XML fragment stream, the average access time significantly depends on the order of fragments in the stream. As such, for query performance, an efficient organization of XML fragment stream is required as well as the indexing for energy-efficient query processing due to the reduction of tuning time. In this paper, a technique of XML fragment stream organization based on query frequencies, fragment size, fragment access frequencies, and an active XML-based indexing scheme are proposed. Through implementation and performance experiments, our techniques were shown to be efficient compared with the conventional XML fragment stream organizations.

• 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 KIISE:Databases
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• v.33 no.1
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• pp.117-128
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• 2006

In this paper, we propose a streaming method for XML data that supports energy-efficient processing of queries over the stream in mobile clients. We propose new stream organizations for XML data which have different kinds of addresses to related data in a stream. We describe event-driven stream generation algorithms for the proposed stream structures and provide search algorithms for simple XML path queries which leverage the access mechanisms incorporated in the stream. Experimental results show that our approaches can effectively improve the tuning time performance of user queries in a wireless broadcasting environment.

• Journal of KIISE:Databases
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• v.33 no.3
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• pp.327-341
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• 2006

As we are getting to deal with more applications that generate streaming data such as sensor network, monitoring, and SDI (selective dissemination of information), active research is being conducted to support efficient processing of queries over streaming data. The applications on the Web environment like SDI, among others, require query processing over streaming XML data, and its investigation is very important because XML has been established as the standard for data exchange on the Web. One of the major problems with the previous systems that support query processing over streaming XML data is that they cannot deal adaptively with dynamically changing stream because they rely on static query plans. On the other hand, the stream query processing systems based on relational data model have achieved adaptiveness in query processing due to query operator routing. In this paper, we propose a system of adaptive query processing over streaming XML data in which the model of adaptive query processing over streaming relational data is applied. We compare our system with YFiiter, one of the representative systems that provide XML stream query processing capability, to show efficiency of our system.

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.27-42
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• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.64-72
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• 2021

XML message brokers have a lot of importance because XML has become a practical standard for data exchange in many applications. Message brokers covered in this document store many users. This paper is a study of the processing of twig pattern queries in XML documents using branching node streams in XML message broker structures. This work is about query processing in XML documents, especially for query processing with XML twig patterns in the XML message broker structure and proposed a method to reduce query processing time when parsing documents with XML twig patterns by processing information. In this paper, the twig pattern query processing method of documents using the branching node stream removes the twigging value of the branch node that does not include the labeling value of the branch node stream when it receives a twig query from the client. In this paper, the leaf node discovery time can be reduced by reducing the navigation time of nodes in XML documents that are matched to leaf nodes in twig queries for client twig queries. Overall, the overall processing time to respond to queries is reduced, allowing for rapid question-answer processing.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.21-29
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• 2012

In ubiquitous computing environment, rising large scale data exchange through sensor network with sharply growing the internet, the processing of the continuous stream data is required. 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 active window sliding using trigger rule. The proposed method is a basic research to control the stream data flow for data mining and continuous query by trigger rules.

• Journal of KIISE:Databases
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• v.36 no.1
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• pp.50-62
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• 2009

In wireless and mobile environments, data broadcasting is recognized as an effective way for data dissemination due to its benefits to bandwidth efficiency, energy-efficiency, and scalability. In this paper, we address the problem of delayed query processing raised by tree-based index structures in wireless broadcast environments, which increases the access time of the mobile clients. We propose a novel distributed index structure and a clustering strategy for streaming XML data which enable energy and latency-efficient broadcast of XML data. We first define the DIX node structure to implement a fully distributed index structure which contains tag name, attributes, and text content of an element as well as its corresponding indices. By exploiting the index information in the DIX node stream, a mobile client can access the wireless stream in a shorter latency. We also suggest a method of clustering DIX nodes in the stream, which can further enhance the performance of query processing over the stream in the mobile clients. Through extensive performance experiments, we demonstrate that our approach is effective for wireless broadcasting of XML data and outperforms the previous methods.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.307-318
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• 2008

One of the primary issues confronting XML message brokers is the difficulty associated with processing a large set of continuous XPath queries over incoming XML seams. This paper proposes a novel system designed to present an effective solution to this problem. The proposed system transforms multiple XPath queries before their run-time into a new region-based data structure, called an XP-table, by sharing their common constraints. An XP-table is matched with a stream relation (SR) transformed from a target XML stream by a SAX parser. This arrangement is intended to minimize the runtime workload of continuous query processing. Also, system performance is estimated and verified through a variety of experiments, including comparisons with previous approaches such as YFilter and LazyDFA. The proposed system is practically linear- scalable and stable for evaluating a set of XPath queries in a continuous and timely fashion.