• Asia pacific journal of information systems
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• v.1 no.1
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• pp.87-101
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• 1991

The primary purpose of this study was to investigate a robust search methodology that could be used in full-text information retrieval systems. A robust search methodology is one that can be easily used by a variety of users (particularly naive users) and it will give them comparable search performance regardless of their different expertise or interests In order to develop a possibly robust search methodology, a fully functional prototype of a fuzzy knowledge based information retrieval system was developed. Also, an experiment that used this prototype information retreival system was designed to investigate the performance of that search methodology over a small exploratory sample of user queries To probe the relatonships between the possibly robust search performance and the query organization using fuzzy inference logic, the search performance of a shallow query structure was analyzes. Consequently the following several noteworthy findings were obtained: 1) the hierachical(tree type) query structure might be a better query organization than the linear type query structure 2) comparing with the complex tree query structure, the simple tree query structure that has at most three levels of query might provide better search performance 3) the fuzzy search methodology that employs a proper levels of cut-off value might provide more efficient search performance than the boolean search methodology. Even though findings could not be statistically verified because the experiments were done using a single replication, it is worth noting however, that the research findings provided valuable information for developing a possibly robust search methodology in full-text information retrieval.

• Journal of Information Technology Applications and Management
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• v.9 no.1
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• pp.27-44
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• 2002

Performance evaluations of database algorithms are usually conducted on a set of queries for a given test database. For more detailed evaluation results, it is often necessary to use different query workloads several times. Each query workload should reflect the querying patterns of the application domain in real world, which are non-uniform in the usage frequencies of attributes in queries of the workload for a given database. It is not trivial to generate many different query workloads manually, while considering non-uniform distributions of attributes'usage frequencies. In this paper we propose a technique to generate non-uniform distributions, which will help construct query workloads more efficiently. The proposed algorithm generates a query-attribute usage distribution based on given constraints on usage frequencies of attributes and qreries. The algorithm first allocates as many attributes to queries as Possible. Then it corrects the distribution by considering attributes and queries which are not within the given frequency constraints. We have implemented and tested the performance of the proposed algorithm, and found that the algorithm works well for various input constraints. The result of this work could be extended to help automatically generate SQL queries for various database performance benchmarking.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1584-1590
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• 2008

The combined query which consists of the region and trajectory query finds trajectories of moving objects which locate in a certain region. The trajectory query is very informant factor to determine query performance because it processes a point query continuously to find predecessors. This results in bad performance due to revisiting nodes in an index. This paper suggests an efficient method for the combined query based on the 3-dimensional R-tree which has good performance of the region query. The basic idea is that we define the least common search line which enables to search single path and a filtering method based on prediction without revisiting nodes.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.123-131
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• 2020

The pattern query in graph database has advantages of easy query expression and high query processing performance compared to relational database SQL. However, unlike the relational database, the graph database may not utilize the advantages of pattern query depending on modeling because the methodology for building the logical data model is not defined. In this study, in the is-a node modeling method that appears during the graph modeling process, we experiment that there is a difference in performance between graph pattern query when designing with a generalization model and designing with a specialization model. As a result of the experiment, it was shown that better performance can be obtained when the is-a node is designed as a specialization model. In addition, when writing a pattern query, we show that if a variable is bound to a node or edge, performance may be better than that of the variable of not bounded. The experimental results can be presented as an is-a node modeling method for pattern query and a graph query writing method in the graph database.

• 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.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.67-79
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• 2007

Recently, to support LBS(location-based services) and telematics applications efficiently, there have been many researches which consider the spatial network instead of Euclidean space. However, existing range query and k-nearest neighbor query algorithms show a linear decrease in performance as the value of radius and k is increased. In this paper, to increase the performance of query processing algorithm, we propose materialization-based range and k-nearest neighbor algorithms. In addition, we make the performance comparison to show the proposed algorithm achieves better retrieval performance than the existing algorithm.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.292-296
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• 2009

The performance of anti-collision algorithm in RFID systems, which are based on FSA algorithm, may be affected by the frame size a query round. In this paper, an anti-collision algorithm with early cancellation of query round is proposed to enhance the performance of EPCglobal Class-1 Gen-2. The Q-algorithm calculates a Q value to determine the next frame size during a query round. In the proposed algorithm, if the new Q value is different from the previous one, the reader transmits a QueryAdjust command to cancel the current query round. The simulation results show that the proposed algorithm can have a stable performance irrespective of the C value of Q-algorithm and the number of tags.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.3-5
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• 2007

Many continuous queries are important to be process efficiently in a data stream environment. It is applied a query index technique that takes linear performance irrespective of the number and width of intervals for processing many continuous queries. Previous researches are not able to support the dynamic insertion and deletion to arrange intervals for constructing an index previously. It shows that the insertion and search performance is slowed by the number and width of interval inserted. Many intervals have to be inserted and searched linearly in a data stream environment. Therefore, we propose Hashed Multiple Lists in order to process continuous queries linearly. Proposed technique shows fast linear search performance. It can be utilized the systems applying a sensor network, and preprocessing technique of spatiotemporal data mining.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.518-532
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• 2017

Due to the rapid growth of the amount of data, research on bigdata processing has been highlighted. For bigdata processing, CUBRID Shard is able to support query processing in parallel way by dividing the database into a number of CUBRID servers. However, CUBRID Shard can answer a user's query only when the query is required to gain accesses to a single CUBRID server, instead of multiple ones. To solve the problem, in this paper we propose a CUBRID based distributed parallel query processing system that can answer a user's query in parallel and distributed manner. Finally, through the performance evaluation, we show that our proposed system provides 2-3 times better performance on query processing time than the existing CUBRID Shard.

• The Transactions of the Korea Information Processing Society
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• v.4 no.4
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• pp.963-972
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• 1997

In imformation retrival, query reformulation algorithms construct querise from a set of intial input and feedback documents, and retrieval performance cna be varied by different sets of input documents. In this study, we developed a criterion for measuring the performance sensitivity of query reformulation algorithms to unput sets. In addition, we also propose a way of mesuring the changes in retrived area, (CIRA) during qucry reformulation. We cimpared CIRAs of query refromulation algorithms (i.e., query tree, DNF method, and Dillon's method) using three test sets:the CACM, CISI, and Medlars. In the experiments, the query tree showed the highest decreasing CIRA during refirmulations, which means the fastest convergence rate to an output set. For sensitivity analysis, the query tree sored the highest sensitivity to different input sets even though its differences to the tther algorithms are very small.