• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.389-392
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• 2002

본 논문에서는 대표적인 NP 문제의 하나인 강의시간표 문제를 분산 제약조건 만족 문제로 해결하는 시스템을 제안한다. 제안한 시스템에서는 복잡하고 방대한 강의시간표 문제를 여러 개의 작은 모듈 단위의 에이전트로 분할한 후 개별 문제외 해를 구하고 이들을 결합시켜 가능해(feasible solution)를 찾는다. 한편, 분리된 에이전트에 의해 해결되는 부-문제들이 상호 의존적이면서 중첩된 경우에 해들 사이의 모순을 해결하면서 최종 해를 구한다. 제안한 시스템에서는 다음과 같은 방법으로 문제를 해결한다. 제약조건을 점진적으로 추가하여 탐색공간을 줄여 나간 후, 국소 탐색을 통해 변수에 일관된 도메인 값을 할당한다. nogood에 대하여 점진적인 제약조건 완화로 탐색공간을 확장하여 모든 변수에 도메인 값을 배정한다. 제약조건 완화는 제약조건들을 몇몇 단계로 정의하고, 휴리스틱 순서와 제약조건의 중요도에 따라 되추적 탐색 기법을 이용하여 순차적으로 완화한다. 만일 과잉-제약조건이 발생할 경우 가중치의 합이 최소로 하는 값을 배정한다. 즉 모든 변수에 도메인 값은 모든 제약조건을 만족하든 초기의 부-문제에 가능해가 될 수 있는 제약조건을 만족해야 한다.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.345-353
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• 2019

Several studies have been proposed to improve storage space efficiency by expressing binary trie data structure as a linear binary bit string. Compact binary tree approach generated using one binary trie increases the key search time significantly as the binary bit string becomes very long as the size of the input key set increases. In order to reduce the key search range, a hierarchical compact binary tree technique that hierarchically expresses several small binary compact trees has been proposed. The search time increases proportionally with the number and length of binary bit streams. In this paper, we generate several binary compact trees represented by full binary tries hierarchically. The search performance is improved by allowing a path for the binary bit string corresponding to the search range to be determined through simple numeric conversion. Through the performance evaluation using the worst time and space complexity calculation, the proposed method showed the highest performance for retrieval and key insertion or deletion. In terms of space usage, the proposed method requires about 67% ~ 68% of space compared to the existing methods, showing the best space efficiency.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.9-11
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• 1999

멀티미디어 DBMS는 연속매체를 서비스할 때 동시에 보다 많은 사용자들에게 일정한 서비스 품질을 유지하면서 서비스를 제공할 수 있어야 한다. 이를 위하여 멀티미디어 DBMS를 위한 저장시스템은 보다 큰 디스크 대역폭을 지원해야 하므로 디스크 배열의 구조를 갖는 것이 바람직하다. 디스크 배열 환경에서 다수의 연속매체를 병행적으로 서비스할 때 요구 데이터를 순차접근에 의하여 검색할 수 있으면 디스크 대역폭을 탐색시간 등으로 소모하지 않으므로 고속 디스크 대역폭을 유지할 수 있다. 또한, 디스크 접근시 디스브 부하 균형을 유지할 수 있으면 자원 활용율이 높은 고성능의 저장 시스템이 될 수 있다. 본 논문에서는 연속매체들을 순차접근에 의해서 처리하면서 디스크 부하 균형을 유지할 수 있는 데이터 배치 기법을 제안한다. 제안한 데이터 배치기법에 의한 성능평가는 모의 실험 전용틀인 AweSim 2.0을 사용하였다.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.652-657
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• 2014

Given a starting point, destination point and various Points Of Interest (POIs), which contain a full or partial order, for a user to visit we wish to create, a sequenced route from the starting point to the destination point that includes one member of each POI type in a particular order. This paper proposes a method for finding the approximate shortest route between the start point, destination point and one member of each POI type. There are currently two algorithms that perform this task but they both have weaknesses. One of the algorithms only considers the distance between the visited POI (or starting point) and POI to visit next. The other algorithm chooses candidate points near the straight-line distance between the start point and destination but does not consider the order of visits on the corresponding network path. This paper outlines an algorithm that chooses the candidate points that are nearer to the network path between the start point and destination using network search. The algorithm looks for routes using the candidate points and finds the approximate shortest route by assigning an adaptive priority to the route that visits more POIs in a short amount of time.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1105-1116
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• 2014

A stochastic rainfall model, NSRPM (Neyman-Scott Rectangular Pulse Model), is able to reflect the cluster characteristics of rainfall events which is unable in the RPM (Rectangular Pulse Model). Therefore NSRPM has advantage in the hydrological applications. The NSRPM consists of five model parameters and the parameters are estimated using optimization techniques such as DFP (Davidon-Fletcher-Powell) method and genetic algorithm. However the DFP method is very sensitive in initial values and is easily converge to local minimum. Also genetic algorithm has disadvantage of long computation time. Nelder-Mead method has several advantages of short computation time and no need of a proper initial value. In this study, the applicability of parameter estimation methods was evaluated using rainfall data of 59 national rainfall networks from 1973-2011. Overall results demonstrated that accuracy in parameter estimation is in the order of Nelder-Mead method, genetic algorithm, and DFP method.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.51-62
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• 2018

High utility sequential pattern (HUSP) mining has been considered as an important research topic in data mining. Although some algorithms have been proposed for this topic, they incur the problem of producing a large search space for HUSPs. The tighter utility upper bound of a sequence can prune more unpromising patterns early in the search space. In this paper, we propose a sequence expected utility (SEU) as a new utility upper bound of each sequence, which is the maximum expected utility of a sequence and all its descendant sequences. A sequence utility list for each pattern is used as a new data structure to maintain essential information for mining HUSPs. We devise an algorithm, high sequence utility list-span (HSUL-Span), to identify HUSPs by employing SEU. Experimental results on both synthetic and real datasets from different domains show that HSUL-Span generates considerably less candidate patterns and outperforms other algorithms in terms of execution time.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.152-154
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• 2000

본 논문에서는 시계열 데이터베이스에서 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘을 제안한다. 정규화 변환은 시계열 데이터간의 절대적인 유클리드 거리에 관계없이, 구성하는 값들의 상대적인 변화 추이가 유사한 패턴을 갖는 시계열 데이터를 검색하는 데에 유용하다. 제안된 알고리즘은 몇 개의 질의 시퀀스 길이에 대해서만 각각 인덱스를 생성한 후, 이를 이용하여 모든 가능한 길이의 질의 시퀀스에 대해서 탐색을 수행한다. 이때, 착오 기각이 발생하지 않음을 증명한다. 본 논문에서는 이와 같이 인덱스가 요구되는 모든 경우 중에서 적당한 간격의 일부에 대해서만 생성된 인덱스를 이용한 탐색 기법을 인덱스 보간법이라 부른다. 질의 시퀀스의 길이 256~512 중 다섯 개의 길이에 대해 인덱스를 생성하여 실험한 결과, 탐색 결과를 선택률이 10-5일 때 제안된 알고리즘의 탐색 성능이 순차 검색에 비하여 평균 14.6배 개선되었다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.1012-1015
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• 2004

There have been several kinds of attempts to actively control the deflected noise behind the noise barrier. Omoto's work in 1993 would be one of the fundamental studies, where he placed the control sources uniformly parallel to the noise barrier. Following this study, Yang pointed that the average distance between the noise source and control sources is more important than the arrangement of control sources such as a straight line or an arc type distribution. In 2004, Baek tried to show optimal arrangement of control sources while keeping the average distance between the noise source and control sources. He used simulated annealing algorithm which is one of the natural algorithms for the selections of optimal control source positions, but the searching technique was a hybrid of the simulated annealing and the sequential searching to adapt to the vast amount of searching time. This study is about the performance comparison between the pure sequential searching and the hybrid one. The simulation results show very similar performance and a pure simulated annealing searching will be more beneficial for the noise reduction performance but at the cost of computing time.