• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1133-1142
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• 2004

This paper proposes a method to classify and retrieve components in repository using the idea of domain orientation for the successful reuse of components. A design pattern was applied to existing systems and a component classification method is suggested here to compare the structural similarity between each component in relevant domain and criterion patterns. Classifying reusable components by their functionality and then depicting their structures with a diagram can increase component reusability and portability between platforms. Efficiency of component reuse can be raised because the most appropriate component to query and similar candidate components are provided in priority by use of-SARM algorithm.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.61-69
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• 2011

Data mining that can not be extracted with a simple query in the form of "useful" means to find information in large databases from the existing and unknown knowledge. It is based on this insight about the data can be defined as a gain. In this paper, we use the Internet to find useful patterns on the Web or saved data to the target Web site, which is to analyze the characteristics of users. A general statistical information on Internet users to the data by applying a relevance analysis, Internet use affect the amount of time to analyze the characteristics of Internet users. Only through experiments extracting data from the association rules, producing optimal results apply for the data pre-processing and algorithm for mining the Web to Internet users. characteristics were analyzed.

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.169-176
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• 2009

Rule discovery is an operation that discovers patterns frequently occurring in a given database. Rule discovery makes it possible to find useful rules from a stock database, thereby recommending buying or selling times to stock investors. In this paper, we discuss storage structures for efficient processing of queries in a system that recommends stock investments. First, we propose five storage structures for efficient recommending of stock investments. Next, we discuss their characteristics, advantages, and disadvantages. Then, we verify their performances by extensive experiments with real-life stock data. The results show that the histogram-based structure improves the query performance of the previous one up to about 170 times.

• Cross-Cultural Studies
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• v.28
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• pp.87-114
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• 2012

The Maa speaking Torobo people inhabiting the southern portion of the Mau Escarpment in Kenya approach both individual and community survival from a relational orientation focused on ethnic identity and responsibility. This social responsibility to the tribe is in stark contrast to Torobo relationships with other ethnic groups. The purpose of the research is twofold. First, the paper explores how folkloric language through a trickster image reflects important cultural and social ideals, understandings, and patterns of thought in Torobo world view. A second purpose is to offer ethnographic information to scholars and students' alike necessary for world view studies of eastern Africa specifically focused on the interplay between anthropomorphic tales and the social context in which these stories are utilized. The key research question for this analysis asks how the trickster image in Torobo folklore conceptualize the life experience. A Torobo folktale entitled, The Clever Hare, is the text chosen for analysis with the hare character as the protagonist. A second query explores the importance of the trickster image in understanding Torobo world view categories of Self and Other. The analysis contributes an ethnographic perspective for the world view categories of Self and Other as well as trickster folklore by examining the nature of Torobo-ness using the tale of the cunning hare as a research tool.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.3
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• pp.365-371
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• 2021

With the rapid growth in Internet users, web applications are becoming the main target of hackers. Most previous WAFs (Web Application Firewalls) target every single HTTP request packet rather than the overall behavior of the attacker, and are known to be difficult to detect new types of attacks. In this paper, we propose a web attack detection system based on user behavior using machine learning to detect attacks of unknown patterns. In order to define user behavior, we focus on features excluding areas where an attacker can camouflage as a normal user. The experimental results shows that by using the path and query information to define users' behaviors, best results for an accuracy of 99% with Decision forest.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.173-184
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• 2002

This paper discuss an index-based subsequence matching that supports time warping in large sequence databases. Time warping enables finding sequences with similar patterns even when they are of different lengths. In earlier work, Kim et al. suggested an efficient method for whole matching under time warping. This method constructs a multidimensional index on a set of feature vectors, which are invariant to time warping, from data sequences. For filtering at feature space, it also applies a lower-bound function, which consistently underestimates the time warping distance as well as satisfies the triangular inequality. In this paper, we incorporate the prefix-querying approach based on sliding windows into the earlier approach. For indexing, we extract a feature vector from every subsequence inside a sliding window and construct a multidimensional index using a feature vector as indexing attributes. For query processing, we perform a series of index searches using the feature vectors of qualifying query prefixes. Our approach provides effective and scalable subsequence matching even with a large volume of a database. We also prove that our approach does not incur false dismissal. To verify the superiority of our approach, we perform extensive experiments. The results reveal that our approach achieves significant speedup with real-world S&P 500 stock data and with very large synthetic data.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.513-524
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• 2006

Normalization transform is very useful for finding the overall trend of the time-series data since it enables finding sequences with similar fluctuation patterns. The previous subsequence matching method with normalization transform, however, would incur index overhead both in storage space and in update maintenance since it should build multiple indexes for supporting arbitrary length of query sequences. To solve this problem, we propose a single index approach for the normalization transformed subsequence matching that supports arbitrary length of query sequences. For the single index approach, we first provide the notion of inclusion-normalization transform by generalizing the original definition of normalization transform. The inclusion-normalization transform normalizes a window by using the mean and the standard deviation of a subsequence that includes the window. Next, we formally prove correctness of the proposed method that uses the inclusion-normalization transform for the normalization transformed subsequence matching. We then propose subsequence matching and index building algorithms to implement the proposed method. Experimental results for real stock data show that our method improves performance by up to $2.5{\sim}2.8$ times over the previous method. Our approach has an additional advantage of being generalized to support many sorts of other transforms as well as normalization transform. Therefore, we believe our work will be widely used in many sorts of transform-based subsequence matching methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.251-258
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• 1998

The purpose of this study is to develop the District-level Planning Support System (DPSS) by using GIS. The district-level planning which is related for district-level control of city, needs the various parcel-level information which is composing the urban physical environment. The information has to be stored and analyzed for recognizing the study area, then the district-level planning will be efficiently managed. The use of GIS in the process of district-level planning is restricted for the creation of thematic map. GIS is not used for the analysis of spatial patterns and planning process. This study evaluates the characteristics of current district-level planning and the basic components of urban physical environment. And the database model is built. The topology among components is defined by using the spatial relationship. Then the spatial query machine for district-level planing is developed by using ArcView 3.1, Avenue and Dialog Extension. This spatial query machine is applied for case study. This study shows 1) the possibility of the district-level planning support system for analyzing spatial relationship, 2) the needs of the up-to-date topographic map showing current building's footlines and the complete integration with cadastral maps, it will reduce the uncertainty in the spatial decision making process, 3) the methodology for the construction of spatial decision making rules, 4) the further study for the using of raster, network, image and three dimension data.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.2
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• pp.51-73
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• 2015

The Web now provides instant access to an unprecedented amount of information that was unthinkable even 20-30 years ago. However, the full potential of the contents available through the Internet can only be realized when one can speak and understand foreign languages, especially English which accounts for more than half of web contents. In this study, we try to investigate the effect of search task languages and task complexity on searching performance. A total of thirty students enrolled at a top private university in Korea were recruited as study subjects. We set up a quasi-experimental design in which thirty subjects are randomly assigned to a set of eight different search tasks containing an equal number of simple and complex tasks and an equal number of tasks in Korean and in English. The results show that there is a significant difference between simple and complex tasks in terms of SERP time, number of queries used, correctness of results and total search time. However, task language does not seem to have affected search performance for this study group. In addition, students with high English proficiency test scores show comparable search performance in English tasks compared with lower test scores. But we note differences in behavioral patterns (different search engines used and search tactics) among the study participants.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.11
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• pp.1031-1040
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• 2010

Hash join is one of the core algorithms in databases management systems. If a hash join cannot complete in one-pass because the available memory is insufficient (i.e., hash table overflow), however, it may incur a few sequential writes and excessive random reads. With harddisk as the tempoary storage for hash joins, the I/O time would be dominated by slow random reads in its probing phase. Meanwhile, flash memory based SSDs (flash SSDs) are becoming popular, and we will witness in the foreseeable future that flash SSDs replace harddisks in enterprise databases. In contrast to harddisk, flash SSD without any mechanical component has fast latency in random reads, and thus it can boost hash join performance. In this paper, we investigate several important and practical issues when flash SSD is used as tempoary storage for hash join. First, we reveal the va patterns of hash join in detail and explain why flash SSD can outperform harddisk by more than an order of magnitude. Second, we present and analyze the impact of cluster size (i.e., va unit in hash join) on performance. Finally, we emperically demonstrate that, while a commerical query optimizer is error-prone in predicting the execution time with harddisk as temporary storage, it can precisely estimate the execution time with flash SSD. In summary, we show that, when used as temporary storage for hash join, flash SSD will provide more reliable cost estimation as well as fast performance.