• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.101-113
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• 2006

A path query is used in XML. Several index structures have been studied for processing the path query efficiently. In recent. the index schemes using suffix tree with structure join method were proposed. ViST is the most representative method among such methods. ViST processes the query using suffix tree and uses B+-tree to reduce the search time of the documents. However, it significantly degrades the search performance when processing the path query. The reason is that it regards the element that is not ancestor-descendant relation in the document as a descendent. In this paper, we propose an efficient index structure to solve the problem of ViST. The query processing method suitable to the index structure is also proposed. It is shown through various experiments that the proposed index structure outperforms the existing index structure in terms of the query processing time.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.709-719
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• 1997

Performance of an algorithm can be mesaurde from serval aspects.Suppose thre is a query formulation al-gorithm.Even though this algorithm shows high retrival performance, ie, high recall and percision, retriveing items can rake a long time.In this study, we time complexity of automatic query reformulation algorithms, named the query Tree, DNF method, and Dillon's method, and comparethem in theoretical and practical aspects using a tral-time performance)the absolute times for each algorithm to fromulate a query)in a Sun SparcStation 2. In experiments using three test sets, CSCM, CISI, and Medlars, the query Tree algorithm was the fastest among the three algorithms tested.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.7
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• pp.809-813
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• 2010

Many studies on reverse skyline query processing have been done for company oriented services. The existing methods about reverse skyline are reverse skyline based on dynamic skyline. There is no reverse skyline query processing algorithm based on metric spaces for location-based services. In this paper we propose a reverse skyline query processing scheme that applies for a general skyline and considers distance spaces. The proposed method processes reverse skyline queries in the metric spaces using the existing spatial indexing scheme and considers both Monochromatic and Bichromatic environments. In order to show the superiority of the proposed scheme, we compare it with the basic skyline query processing scheme through performance evaluation. As a result, the proposed method excellent performance was about 5000 times more than conventional method.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.4
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• pp.157-162
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• 2022

Today, most data is stored in a database (DB). In the DB environment, the users requests the DB to find the data they wants. Similarity Query has predicate that explained by a similarity. However, in the process of processing the similarity query, it is difficult to use an index that can reduce the range of processed records, so the cost of calculating the similarity for all records in the table is high each time. To solve this problem, this paper defines a lightweight similarity function. The lightweight similarity function has lower data filtering accuracy than the similarity function, but consumes less cost than the similarity function. We present a method for reducing similarity query processing cost by using the lightweight similarity function features. Then, Chebyshev distance is presented as a lightweight similarity function to the Euclidean distance function, and the processing cost of a query using the existing similarity function and a query using the lightweight similarity function is compared. And through experiments, it is confirmed that the similarity query processing cost is reduced when Chebyshev distance is applied as a lightweight similarity function for Euclidean similarity.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.165-174
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• 2000

Recent researches about range queries in OLAP are only concerned with applying an aggregation operator over a certain region. However, data analysts in real world need not only the simple range query pattern but also an extended range query pattern that finds ranges which satisfy a special condition specified by using several aggregation operators. In this work, we define the general form of the extended range query and propose an efficient processing method for the 'MAX -of-SUM' query, which is the representative form of the extended range query pattern. The MAX-of-SUM query finds the range which has the maximum range sum value in data cube where the size of the range is given. The proposed query processing method is based on the prediction of the scope of the range sum values. That is, the search space on the query processing can be reduced by using the result of the prediction, and hence, the query response time is also reduced.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.89-97
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• 2011

In semantic web information system like ontology that access distributed information from network, efficient query processing requires an advanced caching mechanism to reduce the query response time. P2P network system have become an important infra structure in web environment. In P2P network system, when the query is initiated, reducing the demand of data transformation to source peer is important aspect of efficient query processing. Caching of query and query result takes a particular advantage by adding or removing a query term. Many of the answers may already be cached and can be delivered to the user right away. In web environment, semantic caching method has been proposed which manages the cache as a collection of semantic regions. In this paper, we propose the semantic caching technique in cluster environment of peers. Especially, using schema data filtering technique and schema similarity cache replacement method, we enhanced the query processing efficiency.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.32-41
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• 1999

In spatial database system, the nearest neighbor query occurs frequently and requires the processing cost higher than other spatial queries do. The number of nodes to be searched in the index can be minimized for optimizing the cost of processing the nearest neighbor query. The optimal search distance is pr9posed for the measurement of a search distance to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we prove properties of the optimal search distance in N-dimensional. We show through experiments that the performance of query processing of our method is superior to other method using maximum search distance.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.85-88
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• 2009

In multimedia database systems, the nearest neighbor Query occurs frequently and requires the processing cost higher than other spatial Queries do. It needs the measurement of search distance that the number of searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the nearest neighbor query. The circular location property of objects is considered to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of nearest neighbor queries be considered a circular location property of object where the search space consists of a circular domain and show its characteristics. The proposed method uses the circular minimum distance and the circular optimal distance, the search measurement for optimizing the processing cost of nearest neighbor queries.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.991-998
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• 2002

With the advent of XML and database languages armed with the object-oriented concept and deductive logic, the problem of efficient query processing for them has become a major issue. We describe a way of processing semi-structured XML data through an implementation of a Deductive and Object-oriented Database (DOODB) language with the explanation of query processing. We have shown how to convert an XML data model to a DOODB data model. We have then presented an efficient query processing method based on Connection Graph Resolution. We also present a knowledge-based query processing method that uses the homomorphism of objects in the database and the associative rule of substitutions.

• The Journal of Information Technology
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• v.12 no.1
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• pp.15-20
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• 2009

In this paper, we aim that it solve to problem of the database hoarding because a week connectivity of wireless networks and cutting of link, Consistency of shared data, optimizing of the log include to Mobile Continuous Query Processing System under the mobile client and server environment. and we demonstrate of the superiority for the new Mobile Continuous Query Processing System compare C-I-S(Client-Intercept -Server)model with performance. and we perform to various experiment in order to establishment of superiority compare the index architecture and method for the realtime Continuous Query Processing. in this paper.