• 대한산업공학회지
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• 제27권1호
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• pp.30-36
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• 2001

We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.

• 정보화연구
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• 제11권2호
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• pp.225-233
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• 2014

오디오 산업은 프리미엄 산업으로써 나날이 발전 하고 있다. 입체 음향 시스템에 관한 연구는 많이 진행 되고 있다. 하지만 Audio database, algorithm, evaluation, metadata scheme 이 모두 각각 이루어지고 있다. 하나의 시스템에서 만들어진 audio 알고리즘을 평가 하고, 저장 할 수 있다면 입체 음향 오디오 연구 발전에 도움이 될 것이다. 그래서 이 논문 에서는 실감형 3D 오디오의 알고리즘을 시스템 적으로 평가 할 수 있는 Database Architecture 제안 하고, 이 Database system 구현을 위하여 XML metadata scheme를 정의 하였다. 본 논문에서는 새로운 오디오 평가 DB를 제시하고, 이를 체계적으로 구현하기 위한 설계를 제시하고자 한다.

• 한국정보과학회논문지:데이타베이스
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• 제34권4호
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• pp.357-368
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• 2007

본 논문에서는 데이타베이스 서버와 모바일 데이타베이스 사이의 데이타 동기화를 위하여 메시지 다이제스트 기반의 SAMD 알고리즘을 제안한다. SAMD 알고리즘은 메시지 다이제스트 테이블을 이용하여 데이타베이스 서버 측과 모바일 데이타베이스 측에 이미지를 만들고 이 두 개의 이미지를 비교하여 동기화가 필요한 로우들을 선별한다. 두 이미지의 값이 다르다면 동기화 정책에 따라 동기화를 진행한다. SAMD 알고리즘은 특정 데이타베이스 밴더에 종속된 기술이나, 트리거, 스토어 프로시져, 타임스탬프등을 사용하지 않고 관계형 데이타베이스의 기본적인 SQL 기능만을 사용한다. 따라서 특정 밴더의 데이타베이스에 종속적이지 않음으로 어떠한 데이타베이스 서버와 모바일 데이타베이스 서버의 조합에도 사용 가능하다. 또한 성능면에서도 기존의 제품에 비해서 우수한 성능을 나타낸다.

• 한국멀티미디어학회논문지
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• 제22권2호
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• pp.225-230
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• 2019

There are several methods which efficiencies of database are uprise. One of the well-known methods is that segments of database satisfying a query was rapidly accessed and processed. So if it is possible to search completely parallel multiple database segment types which satisfy a query, the response time of the query will be reduced. The matter of obtaining CPS(Completely Parallel Searchable) distribution without redundancy can be viewed as graph theoretic problem, and the operation of ring sum on the graph is used for CPS. In this paper, the parallel algorithm is proposed.

• 산업경영시스템학회지
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• 제23권54호
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• pp.1-11
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• 2000

This study suggests the partition algorithm for updating the discovered association rules in large database, because a database may allow frequent or occasional updates, and such update may not only invalidate some existing strong association rules, but also turn some weak rules into strong ones. the Partition algorithm updates strong association rules efficiently in the whole update database reuseing the information of the old large itemsets. Partition algorithms that is suggested in this study scans an incremental database in view of the fact that it is difficult to find the new set of large itemset in the whole updated database after an incremental database is added to the original database. This method of generating large itemsets is different from that of FUP(Fast Update) and KDP(Kim Dong Pil)

• 산업경영시스템학회지
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• 제21권45호
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• pp.121-133
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• 1998

This study suggests an efficient algorithm for updating discovered association rules in large database, because a database may allow frequent or occasional updates, and such updates may not only invalidate some existing strong association rules, but also turn some weak rules into strong ones. FUP and DMI update efficiently strong association rules in the whole updated database reusing the information of the old large item-sets. Moreover, these algorithms use a pruning technique for reducing the database size in the update process. This study updates strong association rules efficiently in the whole updated database reusing the information of the old large item-sets. An updating algorithm that is suggested in this study generates the whole candidate item-sets at once in an incremental database in view of the fact that it is difficult to find the new set of large item-sets in the whole updated database after an incremental database is added to the original database. This method of generating candidate item-sets is different from that of FUP and DMI. After generating the whole candidate item-sets, if each item-set in the whole candidate item-sets is large at an incremental database, the original database is scanned and the support of each item-set in the whole candidate item-sets is updated. So, the whole large item-sets in the whole updated database is found out. An updating algorithm that is suggested in this study does not use a pruning technique for reducing the database size in the update process. As a result, an updating algoritm that is suggested updates fast and efficiently discovered large item-sets.

• 정보기술과데이타베이스저널
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• 제7권2호
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• pp.47-59
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• 2000

In this paper, we analyze the applicability of a general optimization algorithm to a database optimization problem. The index selection problem Is the problem to choose a set of indexes for a database in a way that the cost to process queries in the given workload is minimized subject to a given storage space restriction for storing indexes. The problem is well known in database research fields, and many optimization and/or heuristic algorithms have been proposed. Our work differs from previous research in that we formalize the problem in the form of non-linear Integer Programming model, and investigate the feasibility and applicability of a general purpose optimization algorithm, called OPBDP, through experiments. We implemented algorithms to generate workload data sets and problem instances for the experiment. The OPBDP algorithm, which is a non-linear 0-1 Integer Programming problem solver based on Davis-Putnam method, worked generally well for our problem formulation. The experiment result showed various performance characteristics depending on the types of decision variables, variable navigation methods and ocher algorithm parameters, and indicates the need of further study on the exploitation of the general purpose optimization techniques for the optimization problems in database area.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.280-282
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• 2005

A ribonucleic acid (RNA) is one of the two types of nucleic acids found in living organisms. An RNA molecule represents a long chain of monomers called nucleotides. The sequence of nucleotides of an RNA molecule constitutes its primary structure, and the pattern of pairing between nucleotides determines the secondary structure of an RNA. Non-coding RNA genes produce transcripts that exert their function without ever producing proteins. Predicting the secondary structure of non-coding RNAs is very important for understanding their functions. We focus on Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new traceback matrix and scoring table to improve above algorithm. And the improved algorithm provides better levels of performance than the originals.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.120-125
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• 2000

We propose a semi-automatic and dynamic indexing algorithm for multi-media database(e.g. movie files, audio files), which are difficult to create indexes expressing their emotional or abstract contents, according to user's sensitivity by using user's histories of access to database. In this algorithm, we simply categorize data at first, create a vector space of each user's interest(user model) from the history of which categories the data belong to, and create vector space of each data(title model) from the history of which users the data had been accessed from. By continuing the above method, we could create suitable indexes, which show emotional content of each data. In this paper, we define the recurrence formulas based on the proposed algorithm. We also show the effectiveness of the algorithm by simulation result.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.343-364
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• 2021

In the 5G era, the communication networks tend to be ultra-densified, which will improve the accuracy of indoor positioning and further improve the quality of positioning service. In this study, we propose an indoor three-dimensional (3D) dynamic reconstruction fingerprint matching algorithm (DSR-FP) in a 5G ultra-dense network. The first step of the algorithm is to construct a local fingerprint matrix having low-rank characteristics using partial fingerprint data, and then reconstruct the local matrix as a complete fingerprint library using the FPCA reconstruction algorithm. In the second step of the algorithm, a dynamic base station matching strategy is used to screen out the best quality service base stations and multiple sub-optimal service base stations. Then, the fingerprints of the other base station numbers are eliminated from the fingerprint database to simplify the fingerprint database. Finally, the 3D estimated coordinates of the point to be located are obtained through the K-nearest neighbor matching algorithm. The analysis of the simulation results demonstrates that the average relative error between the reconstructed fingerprint database by the DSR-FP algorithm and the original fingerprint database is 1.21%, indicating that the accuracy of the reconstruction fingerprint database is high, and the influence of the location error can be ignored. The positioning error of the DSR-FP algorithm is less than 0.31 m. Furthermore, at the same signal-to-noise ratio, the positioning error of the DSR-FP algorithm is lesser than that of the traditional fingerprint matching algorithm, while its positioning accuracy is higher.