• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.31-38
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• 2018

As the use of open source databases grows, so does need to evaluate, the performance of search queries for these databases. This paper compares the search query performance of SQL-based open source databases with commercial databases through experiments. The targets are MySql, MariaDB, and MS-SQL Server. In this study, the execution time of various types of search queries are measured. Also, search query performance was experimented according to change of index and number of tuples. Experimental results show that SQL-based open source databases have the potential to replace commercial databases when indexes are used and the number of tuples is not very large.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.355-364
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• 2008

In general, we can use an inverted index for retrieving element lists from structured documents. An inverted index can retrieve a list of elements that have the same tag name. In this approach, however, the cost of query processing is linear to the length of a path query because all the structural relationships (parent-child and ancestor-descendant) should be resolved by structural join operations. In this paper, we propose an inverted index technique and a novel structural join technique for accelerating XML path query evaluation. Our inverted index can retrieve element lists for path segments in a parent-child relationship. Our structural join technique can handle lists of element pairs while the existing techniques handle lists of elements. We show through experiments that these two proposed techniques are integrated to accelerate evaluation of XML path queries.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.320-330
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• 2004

Query languages for XML use paths in a data graph to represent queries. Actually, paths in a data graph are used as a basic constructor of an XML query. User can write more expressive Queries by using Patterns (e.g. regular expressions) for paths. There are many identical paths in a data graph because of the feature of semi-structured data. Current researches for indexing XML utilize identical paths in a data graph, but such an index can grow larger than source data graph and cannot guarantee efficient access path. In this paper we propose a partitioning technique that can partition all the paths in a data graph. We develop an index graph that can find appropriate partitions for a path query efficiently. The size of our index graph can be adjusted regardless of the source data. So, we can significantly improve the cost for index graph traversals. In the performance study, we show our index much faster than other graph based indexes.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.1095-1101
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• 2012

As the amount of data increases explosively, a large scale database system is emerged to store, retrieve and manipulate it. There are several issues in this environments such as, consistency, availability and fault tolerance. In this paper, we address a efficient range-query method where data management services are separated from transaction management services in large-scale database systems. A study had been proposed using partitions to protect independence of two modules and to resolve the phantom problem, but this method was efficient only when range-query is specified by a key. So, we present a new method that can improve the efficiency when range-query is specified by a key attribute as well as other attributes. The presented method can guarantee the independence of separated modules and alleviate overheads for range-query using partial index.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.641-649
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• 2005

As XML is widely used with the development of internet, many researches on the XML storage and query processing have been done Several index techniques have been proposed to efficiently process XML path queries. Recently, structural join has received murk attention as a method to protest the path query. Structural join technique process a path query by identifying the containment relationship of elements. Especially, it has an advantage that we can get the result set by simply comparing related elements only instead of scanning whole document. However during the comparison process, unnecessary elements that are not included in the result set can be scanned. So we propose a new technique, the level structural join. In this technique, we use both the relationship and the level distribution of elements in the path query. Using this technique, we tao improve the performance of query processing only by comparing elements with specific level in the target inverted level.

• Journal of Information Technology and Architecture
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• v.10 no.1
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• pp.123-135
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• 2013

This paper presents a two-dimensional grouping index(2DG-index) for efficient processing of XML filtering queries. Recently, many index techniques have been suggested for the efficient processing of structural relationships among the elements in the XML database such as an ancestor- descendant and a parent-child relationship. However, these index techniques focus on simple path queries, and don't consider the path queries that include a condition value for filtering. The 2DG-index is an index structure that deals with the problem of clustering index entries in the twodimensional domain space that consists of a XML path identifier domain and a filtering data value domain. For performance evaluation, we have compared our proposed 2DG-index with the conventional one dimensional index structure such as the data grouping index (DG-index) and the path grouping index (PG-index). As the result of the performance evaluations, we have verified that our proposed 2DG-index can efficiently support the query processing in XML databases according to the query types.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.453-463
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• 2002

With the prevalence of multi-dimensional data such as images, content-based retrieval of data is becoming increasingly important. To handle multi-dimensional data, multi-dimensional index structures such as the R-tree, Rr-tree, TV-tree, and MVP-tree have been proposed. Numerous research results on how to effectively manipulate these structures have been presented during the last decade. Query processing strategies, which is important for reducing the processing time, is one such area of research. In this paper, we propose query processing algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Both for range query and incremental query, for all dimensional index trees, the response time using VP filtering was always shorter than without VP filtering. We quantitatively showed that VP filtering is closely related with the response time of the query.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.345-354
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• 2005

Subsequence matching is one of the most important operations in the field of data mining. The existing subsequence matching algorithms use only one index, and their performance gets worse as the difference between the length of a query sequence and the site of windows, which are subsequences of a same length extracted from data sequences to construct the index, increases. In this paper, we propose a new subsequence matching method based on index interpolation to overcome such a problem. An index interpolation method constructs two or more indexes, and performs search ing by selecting the most appropriate index among them according to the given query sequence length. In this paper, we first examine the performance trend with the difference between the query sequence length and the window size through preliminary experiments, and formulate a search cost model that reflects the distribution of query sequence lengths in the view point of the physical database design. Next, we propose a new subsequence matching method based on the index interpolation to improve search performance. We also present an algorithm based on the search cost formula mentioned above to construct optimal indexes to get better search performance. Finally, we verify the superiority of the proposed method through a series of experiments using real and synthesized data sets.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.69-77
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• 2009

Stream service environment demands real-time query processing for voluminous data which are ceaselessly delivered from tremendous sources. Typical R-tree based query processing technologies cannot efficiently handle such situations, which require repetitive and inefficient exploration from the tree root on every data event. However, many stream data including sensor readings show high locality, which we exploit to reduce the search space of queries to explore. In this paper, we propose a query processing scheme exploiting the locality of stream data. From the simulation, we conclude that the proposed scheme performs much better than the traditional ones in terms of scalability and exploration efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.492-506
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• 2009

Index structures that are based on sequence matching for XPath processing such as ViST, PRIX and LCS-TRIM have recently been proposed to reduce the search time of XML documents. However, ViST can cause a lot of unnecessary computation and I/O when processing structural joint queries because its numbering scheme is not optimized. PRIX and LCS-TRIM require much processing time for matching XML data trees and queries. In this paper, we propose a novel index structure that solves the problems of ViST and improves the performance of PRIX and LCS-TRIM. Our index structure provides the minimum sequence matching scheme to efficiently process structural queries. Finally, to verify the superiority of the proposed index structure with the minimum sequence matching scheme, we compare our index structure with ViST, PRIX and LCS-TRIM in terms of query processing of a single path or of a branching path including wild-cards ('*' and '//' ).