• 한국군사과학기술학회지
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• 제12권1호
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• pp.18-23
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• 2009

It is hard to find an operation case using anti-submarine searching pattern(ASSP) developed by Korean navy since Korean navy has begun submarine searching operation. This paper proposes the method to develop hull mount sonar(HMS) based optimal submarine searching pattern by using genetic algorithm. Developing the efficient ASSP based on theory in near sea environment has been demanded for a long time. Submarine searching operation can be executed by using ma ulti-step and multi-layed method. however, In this paper, we propose only HMS based ASSP generation method considering the ocean environment and submarine searching tactics as a step of first research. The genetic algorithm, known as a global opination method, optimizes the parameters affecting efficiency of submarine searching operation. Finally, we confirm the performance of the proposed ASSP by simulation.

• 한국지리정보학회지
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• 제12권4호
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• pp.146-157
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• 2009

본 논문은 온톨로지 정보검색 시스템을 구현하기 위해서 Event Process 모델과 디자인 패턴을 이용하여 효과적으로 요구조건에 대해 분석하는 방법에 대해 연구하였다. 이러한 분석 방법은 시스템의 재사용성을 향상시키는 객체지향 프로세스 모델에 대한 기법과 사용자의 더 많은 정보의 획득을 위한 것이다. 우리는 이러한 온톨로지 데이터의 재사용성에 대한 분석 방법을 제안하고자 한다. 본 논문에서 온톨로지에 기반한 데이터의 검색은 사용자에게 정확한 정보의 획득을 보여준다. 또한 관리모듈을 통한 온톨로지 데이터의 관리를 통해서 온톨로지의 재사용성을 보여주었고, 기존 다른 데이터와의 연동 및 공유를 할 수 있다. 따라서, 객체지향 설계 유형에 의한 온톨로지 기반 정보검색 시스템은 높은 안정성과 신뢰성을 보여주고, 모듈 및 소프트웨어의 재사용과 확장성을 높이며 사용자에게 신뢰도 있는 정보를 보여주는데 기여 할 것이다.

• 한국문헌정보학회지
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• 제44권4호
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• pp.95-114
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• 2010

Multimedia searching is an important activity on the Web, especially among the younger generation. The purpose of this study aims to examine college students’ multimedia information needs and searching on the Internet. While there is a clear pattern among students with respect to their multimedia uses, searching sources, relevance criteria and searching barriers, some differences exist especially according to searching of different multimedia types such as image, audio and video. For multimedia uses, information/data-focused uses are frequently found in image and video, while the use of audio is mainly for object-focused searches. As multimedia searching sources, audio and video files present a similar pattern of being high in media specific searching sources and low in generic search engines. Browsing through related blogs and homepages is an important part of searching for media files accounting for approximately 20% of total search for each media. The relevance criteria used by study participants when search for image files was primarily concerned with topicality while the contextual and media quality in the audio and video types are also considered important. Searching barriers for audio and video files are categorized into three broad aspects, including access and search quality, preview limitations and collection limitations, while obstacles for image files searching include access difficulties and low qualities of various collection.

• 한국의류산업학회지
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• 제13권5호
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• pp.734-742
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• 2011

This study has been undertaken as a basic research for automatic pattern design for baseball uniforms manufactured under custom-MTM system, propose building up of a system whereby various partial patterns are combined under an automatic design system and develop a multi-combination type pattern searching algorithm which allows development of a various designs. As a result of this, type classification based on pattern design elements includes side, open, collar, facing and panel type. Design have been divided into coarse classification ranging from level 1 to 7 according to pattern design elements, based on a design distribution chart. Out of 7 such levels, 3 major types determining design which are, more specifically, level 1 sleeve type, level 2 open type and level 3 collar type, have been taken and combined to determine a total of 12 types to be used for design classification codes. Respective name of style and patterns have been coded using alphabet and numerals. Totally, pattern searching algorithm of multi-combination type has been developed whereby combination of patterns belonging to a specific style can be retrieved automatically once that style name is designated on the automatic pattern design system.

• 한국멀티미디어학회논문지
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• 제5권5호
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• pp.590-598
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• 2002

효율적인 순차패턴 마이닝을 위해서는 후보패턴의 생성 비용을 줄이고 동시에 생성된 후보패턴에 대한 탐색공간을 줄여야 한다. 그러나 이전에 개발된 알고리즘들은 이러한 문제들을 효율적으로 해결하지 못하고 있다. 특히 Apriori-like 방법들은 알고리즘은 단순하지만 많은 크기의 후보패턴 집합생성, 대용량 데이터 베이스의 반복적인 탐사 등의 문제점이 있고, PrefixSpan[2]은 단계별로 분할된 프레픽스 프로젝티드(prefix projected) 데이터 베이스들을 구성 하여 후보패턴의 지지도 계산을 위한 탐색 공간을 줄이지만 프로젝티드 데이타베이스들의 구성비용이 크다는 문제점이 있다. 이러한 문제점들의 개선을 위해 본 논문에서는 새로운 순차패턴 마이닝 방법인 Suffixspan(Suffix Checked Sequential Pattern mining)을 제 안한다. Suffixspan은 순차패턴 집합의 단계별 분할특성과 서픽스(suffix) 특성을 이용하여 적은 비용으로 작은 크기의 후보패턴 집합을 생성하고, 1-프레픽스 프로젝티드 데이타베이스를 구성하여 후보패턴 검사를 위한 탐색공간을 줄인다.

• 한국경영과학회지
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• 제39권1호
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• pp.29-48
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• 2014

The recent keyword advertising does not reflect the individual customer searching pattern because it is focused on each keyword at the aggregate level. The purpose of this research is to observe processes of customer searching patterns. To be specific, individual deal-proneness is mainly concerned. This study incorporates location as a control variable. This paper examines the relationship between customers' searching patterns and probability of purchase. A customer searching session, which is the collection of sequence of keyword queries, is utilized as the unit of analysis. The degree of deal-proneness is measured using customer behavior which is revealed by customer searching keywords in the session. Deal-proneness measuring function calculates the discount of deal prone keyword leverage in accordance with customer searching order. Location searching specificity function is also calculated by the same logic. The analyzed data is narrowed down to the customer query session which has more than two keyword queries. The number of the data is 218,305 by session, which is derived from Internet advertising agency's (COMAS) advertisement managing data and the travel business advertisement revenue data from advertiser's. As a research result, there are three types of the deal-prone customer. At first, there is an unconditional active deal-proneness customer. It is the customer who has lower deal-proneness which means that he/she utilizes deal-prone keywords in the last phase. He/she starts searching a keyword like general ones and then finally purchased appropriate products by utilizing deal-prone keywords in the last time. Those two types of customers have the similar rates of purchase. However, the last type of the customer has middle deal-proneness; who utilizes deal-prone keywords in the middle of the process. This type of a customer closely gets into the information by employing deal-prone keywords but he/she could not find out appropriate alternative then would modify other keywords to look for other alternatives. That is the reason why the purchase probability in this case would be decreased Also, this research confirmed that there is a loyalty effect using location searching specificity. The customer who has higher trip loyalty for specificity location responds to selected promotion rather than general promotion. So, this customer has a lower probability to purchase.

• 컴퓨터교육학회논문지
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• 제5권4호
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• pp.53-60
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• 2002

GSP와 같은 Apriori-like 순차패턴 마이닝 방법들은 마이닝 과정에서 많은 후보패턴들을 생성하고, 대용량 데이타베이스의 반복적인 탐색을 필요로 하는 문제점이 있다. 그리고 후보패턴들의 탐색공간을 줄이기 위해 단계별로 프레픽스-프로젝티드 (prefix-projected) 데이터베이스를 구성하는 PrefixSpan 방법은 탐색공간을 줄이지만 프로젝티드 데이터베이스의 구성비용이 문제가 된다. 효율적인 순차패턴 마이닝을 위해서는 후보패턴의 생성비용과 탐색공간을 모두 줄여야 한다. 본 논문에서는 이를 위한 새로운 순차패턴 마이닝 방법인 SuffixSpan(Suffix checked Sequential Pattern mining)을 설명하고, 이에 대한 형식적 접근을 보인다.

• 대한의용생체공학회:의공학회지
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• 제14권2호
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• pp.185-193
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• 1993

In this paper, the peak detection algorithm was developed for the purpose of screening of the target compounds. Algorithm is divided into searching the characteristic ion and peak detection. The heuristic knowledge about analytical chemistry was applied for the searching the characteristic ion. Peak detection was accomplished in comparison with the peak identification strings and pattern strings around the retention time. Pattern strings are composed with the number which generated by pattern identification function. The variables of pattern identification function are the codes which represent the difference of two adjacent abundances Some of the free steroids were selected to demonstrate the proposed algorithm.

• Journal of Information Technology Applications and Management
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• 제26권1호
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• 컴퓨터교육학회논문지
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• 제6권1호
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• pp.1-8
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• 2003

본 논문에서는 frequent itemset을 빠르게 발견해내기 위한 효율적인 vertical 마이닝 알고리즘을 제안한다. 본 알고리즘은 frequent itemset을 구하기 위해 아이템들을 Least Support Itemset(LSI) 과의 유사도에 의해 올림차순으로 정렬하여 탐색 트리를 구축하여 보다 빠르고 효율적으로 frequent itemset을 찾아낸다. 또한, 트리를 탐색 시, 2가지의 휴리스틱 방법을 사용하여 탐색의 초기에 많은 후보 아이템들을 탐색 트리로부터 제거함으로써 탐색 공간을 크게 줄인다. 본 논문에서 제안하는 알고리즘은 이전의 알고리즘들과 비교해, long pattern을 가지는 데이터 베이스에서 보다 빠르게 frequent itemset을 발견해 냄을 실험을 통해 발견하였다.