• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.51-54
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• 2005

This paper proposes an index structure which is used to process X-Path on S-XML data. There are many previous index structures based on tree structure for X-Path processing. Because of general tree index's top-down query fashion, the unnecessary node traversal makes heavy access and decreases the query processing performance. And both of the two query types for X-Path called single-path query and branching query need to be supported in proposed index structure. This method uses a combination of path summary and the node indexing. First, it manages hashing on hierarchy elements which are presented in tag in S-XML. Second, array blocks named path summary array is created in each node of hashing to store the path information. The X-Path processing finds the tag element using hashing and checks array blocks in each node to determine the path of query's result. Based on this structure, it supports both single-path query and branching path query and improves the X-Path processing performance.

• Journal of Digital Contents Society
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• v.10 no.2
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• pp.239-247
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• 2009

In simple topology in network system, query should be delivered to all linked peers for query processing. This causes waste of transmission band width and throughput of each peer. To overcome this, as well as query processing strategy, efficient routing technique to deliver query to proper peer is needed. For efficient routing, clustering of peers in P2P networks is important. Clustering of P2P network bases on that combines peers that have similar characteristics in same cluster reduces quantity of message in network than assign peer for cluster randomly. In this paper, we propose clustering techniques for ontology based P2P query processing. Similarity measure point, cluster index structure, and query processing steps in ontology based P2P cluster environment are proposed.

• Journal of Information Processing Systems
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• v.5 no.4
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• pp.229-236
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• 2009

Sensors are deployed to gather physical, environmental data in sensor networks. Depending on scenarios, it is often assumed that it is difficult for batteries to be recharged or exchanged in sensors. Thus, sensors should be able to process users' queries in an energy-efficient manner. This paper proposes a spatial query processing scheme- Minimum Bounding Area Based Scheme. This scheme has a purpose to decrease the number of outgoing messages during query processing. To do that, each sensor has to maintain some partial information locally about the locations of descendent nodes. In the initial setup phase, the routing path is established. Each child node delivers to its parent node the location information including itself and all of its descendent nodes. A parent node has to maintain several minimum bounding boxes per child node. This scheme can reduce unnecessary message propagations for query processing. Finally, the experimental results show the effectiveness of the proposed scheme.

• Journal of Computing Science and Engineering
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• v.3 no.1
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• pp.27-58
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• 2009

Aggregation join queries are an important class of queries over data streams. These queries involve both join and aggregation operations, with window-based joins followed by an aggregation on the join output. All existing research address join query optimization and aggregation query optimization as separate problems. We observe that, by putting them within the same scope of query optimization, more efficient query execution plans are possible through more versatile query transformations. The enabling idea is to perform aggregation before join so that the join execution time may be reduced. There has been some research done on such query transformations in relational databases, but none has been done in data streams. Doing it in data streams brings new challenges due to the incremental and continuous arrival of tuples. These challenges are addressed in this paper. Specifically, we first present a query processing model geared to facilitate query transformations and propose a query transformation rule specialized to work with streams. The rule is simple and yet covers all possible cases of transformation. Then we present a generic query processing algorithm that works with all alternative query execution plans possible with the transformation, and develop the cost formulas of the query execution plans. Based on the processing algorithm, we validate the rule theoretically by proving the equivalence of query execution plans. Finally, through extensive experiments, we validate the cost formulas and study the performances of alternative query execution plans.

• 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.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.44-53
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• 2008

According to the widespread use of ontology-based applications, it is critical to efficiently store and process semantic information. Even though several related systems have been developed, they have some limitations in perspectives of the volume of target semantic data, the performance of semantic query processing, and the semantic data maintenance. In this paper we propose the OWL-aware relational model for the ontology management system and SQL-based semantic query processing mechanism. Also, to verify the query processing performance, we show that the proposed query professing mechanism is more efficient than sesame.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.6
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• pp.397-401
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• 2007

Recent applications on continuous queries on moving objects are extended quickly to various parts. These applications need not only 2-dimensional space data but also high-dimensional space data. If we use previous index for overlapped continuous range queries on high-dimensional space data, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We focus on stationary queries, non-exponential increase of storage cost and efficient processing time for large data sets. In this paper, to solve these problems, we present a novel query indexing method, denoted as PAB(Projected Attribute Bit)-based query index. We transfer information of high-dimensional continuous range query on each axis into one-dimensional bit lists by projecting technique. Also proposed query index supports incremental update for efficient query processing. Through various experiments, we show that our method outperforms the CES(containment-encoded squares)-based indexing method which is one of the most recent research.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.30-42
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• 2015

In this paper, we propose a new skyline query processing scheme to enhance accuracy of query processing and communication cost in mobile P2P environments. The proposed scheme consists of three stages such as the pre-skyline processing, the query transmission range extension policy, and the continuous skyline query processing. In the pre-skyline processing, a peer selects the candidate filtering objects who have the potential to be selected. By doing so, the proposed scheme reduces the filtering cost when processing the query. In the query transmission range extension policy, we have improved the accuracy by extending the query transmission range. In addition, it can handle continuous skyline query by performing the monitoring after the first skyline query processing. In order to show the superiority of the proposed method, we compare it with the existing schemes through performance evaluation. As a result, it was shown that the proposed scheme outperforms the existing schemes.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1429-1432
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• 2003

This paper addresses the problem of finding a constrained nearest neighbor for moving query point(we call it CNNMP) The Nearest neighbor problem is classified by existence of a constrained region, the number of query result and movement of query point and target. The problem assumes that the query point is not static, as 1-nearest neighbor problem, but varies its position over time to the constrained region. The parameters as NC, NCMBR, CQR and QL for the algorithm are also presented. We suggest the query optimization algorithm in consideration of topological relationship among them

• 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.