• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.411-425
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• 2000

Information retrieval systems for structured documents which are written in SGML or XML support partial retrieval of document. In order to efficiently process queries based on document structures, low memory overhead for indexing, quick response time for queries, supports to powerful types of user queries, and minimal updates of index structure for document updates are required. This paper suggests the Global Document Instance Tree(GDIT) and proposes an effective indexing scheme and query processing algorithms based on the GDIT. The indexing scheme keeps up indexing and retrieval effciency and also guarantees minimal updates of the index structure when document structures are updated.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.148-157
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• 2002

Caching in meta-search engines can improve the response time of users' request. We describe the cache scheme in our meta-search engine in terms of its architecture and operational flow. In particular, we propose a popularity-driven cache algorithm that utilizes popularities of queries to determine cached data to be purged. The popularity is a value that represents the normalized occurrence frequency of user queries. This paper presents how to collect popular queries and how to calculate query popularities. An empirical performance evaluation of the popularity-driven caching with the traditional schemes (i.e., least recently used (LRU) and least frequently used (LFU)) has been carried out on a collection of real data. In almost all cases, the proposed replacement policy outperforms LRU and LFU.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.15-23
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• 2020

While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.25-33
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• 2013

The procedure of the arbitration which is the tag collision is essential because the multiple tags response simultaneously in the same frequency to the request of the Reader. This procedure is known as Anti-collision and it is a key technology in the RFID system. In this paper, we propose the 4-Bit Pattern Slot Allocation(4-BPSA) algorithm for the high-speed identification of the multiple tags. The proposed algorithm is based on the tree algorithm using the time slot and identify the tag quickly and efficiently through accurate prediction using the a slot as a 4-bit pattern according to the slot allocation scheme. Through mathematical performance analysis, We proved that the 4-BPSA is an O(n) algorithm by analyzing the worst-case time complexity and the performance of the 4-BPSA is improved compared to existing algorithms. In addition, we verified that the 4-BPSA is performed the average 0.7 times the query per the Tag through MATLAB simulation experiments with performance evaluation of the algorithm and the 4-BPSA ensure stable performance regardless of the number of the tags.

• Journal of KIISE
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• v.42 no.10
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• pp.1247-1253
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• 2015

An inverted index structure is widely used for efficient string similarity search. One of the main requirements of similarity search is a fast response time; to this end, most techniques use an in-memory index structure. Since the size of an inverted index structure usually very large, however, it is not practical to assume that an index structure will fit into the main memory. To alleviate this problem, we propose a novel technique that reduces the size of an inverted index. In order to reduce the size of an index, the proposed technique rearranges data strings so that the data strings containing the same q-grams can be placed close to one other. Then, the technique encodes those multiple strings into a range. Through an experimental study using real data sets, we show that our technique significantly reduces the size of an inverted index without sacrificing query processing time.

• Journal of Korea Multimedia Society
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• v.10 no.4
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• pp.421-431
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• 2007

Due to the rapid development of wireless communication technology, demands on data services in mobile computing environment are gradually increasing. In mobile computing environments, a mobile host began to use cache to overcome the weak point. Caching at mobile host could reduce the bandwidth consumption and query response time, but mobile host must maintain cache consistency. In this paper, we propose a cache consistency strategy to consider the period of data usage. The server allows an effective broadcasting by classifying data into two groups of periodic and non-periodic. By classifying the data, it prevent from elimination of cache after disconnection of periodic data by using expired time. By storing IR(Invalidation Report) messages, this scheme divides cached data by selection after disconnection. Consequently, we have shown much improvement in total consumption of bandwidth than the conventional scheme.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2273-2286
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• 2000

In order to acquire the precise and fast response for an analytical query, proper selection of the views to materialize in data warehouse is very crucial. In traditional view selection algorithms, the whole relations are considered to be selected as materialized views. However, materializing the whole relations rather than a part of relations results in much worse performance in terms of time and space cost. Therefore, we present an improved algorithm for selection of views to materialize using clustering method to overcome the problem resulted from conventional view selection algorithms. In the presented algorithm, ASVMRT(Algorithm for Selection of Views to daterialize using Iteduced Table). we first generate reduced tables in clata warehouse using automatic clustering based on attrihute-values density, then we consider the combination of reduced tables as materialized views instead of the combination of the original hase relations. For the justification of the proposecl algorithm. we show the experimental results in which both time and space cost are approximately 1.8 times better than the conventional algorithms.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.665-676
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• 2001

The most expensive spatial operation in patial database in a spatial join which computes a combined table of which tuple consists of two tuples of the two tables satisgying a spatial predicate. Although the execution time of sequential processing of a spatial join has been so far considerably improved the response time is not tolerable because of not meeting the requiremetns of interactive users. It is usually appropriate to use parallel processing to improve the performance of spatial join processing. in spatial database the fixed grids which consist of the regularly partitioned cells can be employed the previous works on the spatial joins have not studied the parallel processing of spatial joins using fixed grids. This paper has presented an analytical cost model that estimates the comparative performance of a parallel spatial join algorithm based on the fixed grids in terms of the number of MBR comparisons. disk accesses, and message passing, Several experiments on the synthetic and real datasets show that the proposed analytical model is very accurate. This most model is also expected to used for implementing a very important DBMS component, Called the query processing optimizer.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.04a
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• pp.28-35
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• 2000

In order to acquire the precise and fast response for an analytical query, proper selection of the views to materialize in data warehouse is very crucial. In traditional algorithms, the whole relation is considered to be selected as materialized views. However, materializing the whole relation rather than a part of relation results in much worse performance in terms of time and space cost. Therefore, we present a new algorithm for selection of views to materialize using clustering method in order to improve the performance of data warehouse including this problem. In the presented algorithm, ASVMR(Algorithm for Selection of Views to Materialize using Reduced table), we first generate reduced tables in data warehouse using automatic clustering based on attribute-values density, then we consider the combination of reduced tables as materialized views instead of the combination of the original base relations. We also show the experimental results in which both time and space cost are approximately 1.8 times better than the conventional algorithms.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.147-152
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• 2019

Infrastructure is rapidly growing as Internet business grows with the latest IT technologies such as IoT, BigData, and AI. However, in most companies, a limited number of people need to manage a lot of hardware and software. Therefore, Polestar Enterprise Management System(PEMS) is applied to monitor the system operation status, IT service and key KPI monitoring. Real-time monitor screening prevents system malfunctions and quick response. With PEMS, you can see configuration information related to IT hardware and software at a glance, and monitor performance throughout the entire end-to-end period to see when problems occur in real time.