• Journal of Korea Society of Industrial Information Systems
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• v.8 no.2
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• pp.45-53
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• 2003

The significances of this paper are of two points. One is that this research develops the query expansion search by adding the related terms based on the dictionary to the original query terms. This method shortens the process of the conventional model of query expansion utilizing the feedback data of the search. The other is that this research tries to find out the optimal point of precisions and recalls by differentiating the weight ratio between original quay and additional terms. This method shows that the efficiency and precision of query expansion search increase.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.92-96
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• 2011

Nowadays, the researches study high rate and real-time query applications seem to be real-time query scheduling protocols and energy aware real time query protocols. Also the WSNs should provide the quality of data in real time query applications that is more and more popular for wireless sensor networks (WSNs). Thus we propose the quality of data function to merge into energy efficiency called energy join quality aware realtime query scheduling (EJQRTQ). Our work calculate the energy ratio that considers interference of queries, and then compute the expected quality of query and allocate slots to real-time preemptive query scheduler.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.2
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• pp.113-119
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• 2000

In this paper, we design and implement a query processor of real-time main memory database systems, which reflect the characteristics of main memory database systems and satisfy timing constraints. The proposed query processor manages real-time data that has timing constraint by exploiting meta database. It supports CLI in order to make application programs. It also supports extended CLI and stored CLI. The former can be expressed the Information on real-time transaction. The latter is designed to support frequently processed transaction. The proposed query processor is implemented as query processor of real-time database management systems. We Present performance evaluation results that illustrate ratio of transaction, which satisfy deadline are increased by the query processing ability of system and the efficient management of real-time data.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.195-210
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• 2007

Dwarf is a highly compressed structure, which compresses the cube by eliminating the semantic redundancies while computing a data cube. Although it has high compression ratio, Dwarf is slower in querying and more difficult in updating due to its structure characteristics. We all know that the original intention of data cube is to speed up the query performance, so we propose two novel clustering methods for query optimization: the recursion clustering method which clusters the nodes in a recursive manner to speed up point queries and the hierarchical clustering method which clusters the nodes of the same dimension to speed up range queries. To facilitate the implementation, we design a partition strategy and a logical clustering mechanism. Experimental results show our methods can effectively improve the query performance on data cubes, and the recursion clustering method is suitable for both point queries and range queries.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.773-780
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• 2005

If XML queries are expanded based on ontology, broader search may be possible. On the other hand, queries that are not adequate to target documents may also degrade the search efficiency. We try to improve query adequacy by expanding query based on a reduced ontology, which is the result of ontology and target DTD match. The match considers ontology concepts and DTD elements as well as ontology and DTD attributes. Since the reduced ontology can improve the hit ratio of queries and also be successively reusable for XML documents of a kind, the proposed method can improve XML search efficiency.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.1
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• pp.35-50
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• 2004

This study evaluated the applicability of the static hierarchic clustering model to clustering query results in OPAC. Two clustering methods(Between Average Linkage(BAL) and Complete Linkage(CL)) and two similarity coefficients(Dice and Jaccard) were tested on the query results retrieved from 16 title-based keyword searchings. The precision of optimal dusters was improved more than 100% compared with title-word searching. There was no difference between similarity coefficients but clustering methods in optimal cluster effectiveness. CL method is better in precision ratio but BAL is better in recall ratio at the optimal top-level and bottom-level clusters. However the differences are not significant except higher recall ratio of BAL at the top-level duster. Small number of clusters and long chain of hierarchy for optimal cluster resulted from BAL could not be desirable and efficient.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.794-804
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• 2008

In this paper, we analyze the performance of probabilistic slotted anti-collision algorithm used in EPCglobal Class-1 Generation-2 (Gen2). To increase throughput and system efficiency, and to decrease tag identification time and collision ratio, we propose new tag anti-collision algorithms, which are FAFQ (fired adjustable flamed Q) algorithm and AAFQ (adaptive adjustable framed Q) algorithm, by using QueryAdjust command. We also propose grouping method based on Gen2 to improve the efficiency of tag identification. The simulation results show that all the proposed algorithms outperform Q algorithm, and AAFQ algorithm performs the best. That is, AAFQ has an increment of 5% of system efficiency and a decrement of 4.5% of collision ratio. For FAFQ and AAFQ algorithm, the performance of grouping method is similar to that of ungrouping method. However, for Q algorithm in Gen2, grouping method can increase throughput and system efficiency, and decrease tag identification time and collision ratio compared with ungrouping method.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.79-88
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• 2009

The volume of memory to store real-time data stream is varied dynamically. Continuous queries processing the data stream must manage the storage volume dynamically. In previous research, according to current volume of data a general memory manager which allocates and releases memory by a page unit is researched.However, the method frequently executes page allocation and release to store data stream. Moreover, particularly delayed queries can monopolize many of pages because the method directly allocates pages when a query has not enough memory. Focusing on the problems in memory management systems, this research proposes a memory management method which reduces the frequency of allocation and release and uniformly distributes pages for queries. The method can reduce the frequency of allocation and release through allocation based on utilization ratio of pages in each query and prevent memory monopoly through memory allocation which considers query delay.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8370-8377
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• 2015

In spatial data stream management systems, it is needed appropriate load shedding algorithm because real-time input spatial data streams could exceed the limitation of main memory. However previous researches, lack regard for input ratio and spatial utilization rates of spatial data streams, or the characteristics of data source which generates data streams with spatial information efficiently, can lead to decrease the performance and accuracy of spatial data stream query. Therefore, multi-level load shedding scheme for spatial data stream management systems is proposed to increase the spatial query performance and accuracy. This proposed scheme limits overloads in relation to the input rate and the characteristics of data source first, and then, if needed, query data representing low query participation probability based on spatial utilizations are dropped relatively. Our experiments show that the proposed method could decrease load shedding frequency for previous researches by more than 11% despite query results accuracy and query performance are superior at 0.04% and 3%.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.44-57
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• 2002

Multiple spatial queries are defined as two or more spatial range queries to be executed at the same time. The primary processing of internet-based map services is to simultaneously execute multiple spatial queries. To improve the throughput of multiple queries, the time of disk I/O in processing spatial queries significantly should be reduced. The declustering scheme of a spatial dataset of the MIMD architecture cannot decrease the disk I/O time because of random seeks for processing multiple queries. This thesis presents query scheduling strategies to ease the problem of inter-query random seeks. Query scheduling is achieved by dynamically re-ordering the priority of the queued spatial queries. The re-ordering of multiple queries is based on the inter-query spatial relationship and the latency of query processing. The performance test shows that the time of multiple query processing with query scheduling can be significantly reduced by easing inter-query random seeks as a consequence of enhanced hit ratio of disk cache.