• Proceedings of the IEEK Conference
• /
• 2002.06c
• /
• pp.99-102
• /
• 2002

K-means clustering algorithm is a very popular clustering technique, which is used in the field of information retrieval. In this paper, We deal with the problem of K-means Algorithm from the view of creating the centroids and suggest a method reflecting document feature and considering the context of each document to determine the new centroids during the process of forming new centroids. For experiment, We used the automatic document summarizer to summarize the Reuter21578 newslire test dataset and achieved 20% improved results to the recall metrics.

• Korean Journal of Oriental Medicine
• /
• v.12 no.3 s.18
• /
• pp.1-15
• /
• 2006

For the recent several years, there has been much interest in lexical semantic network. However, it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic word clustering systems, which are called system A and system B respectively. 68,455,856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3,656 '-ha' verbs. The target data is the 'multilingual Word Net-CoreNet'.When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A, 45.3%.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.6
• /
• pp.99-108
• /
• 2004

In this paper, a new fast detection and clutter rejection method is proposed for CCD-image-based Automatic Target Detection System. For defence application, fast computation is a critical point, thus we concentrated on the ability to detect various targets with simple computation. In training stage, 1D template set is generated by regional vertical projection and K-means clustering, and binary tree structure is adopted to reduce the number of template matching in test stage. We also use adaptive skip-width by Correlation-based Adaptive Predictive Search(CAPS) to further improve the detecting speed. In clutter rejection stage, we obtain Fourier Descriptor coefficients from boundary information, which are useful to rejected clutters.

• The KIPS Transactions:PartD
• /
• v.13D no.2 s.105
• /
• pp.207-214
• /
• 2006

Though the number of completely sequenced genomes quickly grows in recent years, the methods to predict protein functions by homology from the genomes have not been used sufficiently. It has been a successful technique to construct an OPCs(Orthologous Protein Clusters) with the best reciprocal BLAST hits from multiple complete-genomes. But it takes time-consuming-processes to make the OPCs with manual work. We, here, propose an automatic method that clusters OPs(Orthologous Proteins) from multiple complete-genomes, which is, to be extended, based on INPARANOID which is an automatic program to detect OPs between two complete-genomes. We also Prove all possible clustering mathematically.

• Phonetics and Speech Sciences
• /
• v.6 no.1
• /
• pp.77-83
• /
• 2014

This paper proposes a speaker and environment clustering method in order to overcome the degradation of the speech recognition performance caused by various noise and speaker characteristics. In this paper, instead of using the distance between Gaussian mixture model (GMM) weight vectors as in the Google's approach, the distance between the adapted mean vectors based on the modified maximum a posteriori (MAP) adaptation is used as a distance measure for vector quantization (VQ) clustering. According to our experiments on the simulation data generated by adding noise to clean speech, the proposed clustering method yields error rate reduction of 10.6% compared with baseline speaker-independent (SI) model, which is slightly better performance than the Google's approach.

• International Journal of Contents
• /
• v.2 no.3
• /
• pp.11-17
• /
• 2006

The Clustering is representative method of components classification. The previous clustering methods that use cohesion and coupling cannot be effective because design pattern has focused on relation between classes. In this paper, we classified design patterns with features of object-oriented relationship. The result is that classification by clustering showed higher precision than classification by facet. It is effective that design patterns are classified by automatic clustering algorithm. When patterns are retrieved in classification of design patterns, we can use to compare them because similar pattern is saved to same category. Also we can manage repository efficiently because of storing patterns with link information.

• Journal of Korea Water Resources Association
• /
• v.42 no.8
• /
• pp.659-671
• /
• 2009

Fuzzy c-means clustering technique is applied to improve the accuracy of G/R ratio used for rainfall estimation by radar reflectivity. G/R ratio is computed by the ground rainfall records at AWS(Automatic Weather System) sites to the radar estimated rainfall from the reflectivity of Kwangduck Mt. radar station with 100km effective range. G/R ratio is calculated by two methods: the first one uses a single G/R ratio for the entire effective range and the other two different G/R ratio for two regions that is formed by clustering analysis, and absolute relative error and root mean squared error are employed for evaluating the accuracy of radar rainfall estimation from two G/R ratios. As a result, the radar rainfall estimated by two different G/R ratio from clustering analysis is more accurate than that by a single G/R ratio for the entire range.

• Journal of the Korean Geographical Society
• /
• v.41 no.1 s.112
• /
• pp.121-135
• /
• 2006

Even though the similar land price zone is very important element in the public land appraisal procedure, the concept is implicitly described and applied into the actual land appraisal system. This situation makes it worse when applying for the automatic selection of a comparative standard land parcel. In addition, the division of similar land price zones requires the objective and reasonable process for improving ALPAS(Automatic land Price Appraisal System), which becomes an issue today. To solve the similar land price zone determination problem that is caused by the lack of objective numerical standard, this study proposed a similar land price zone determination method using a hybrid clustering technique. Results showed that this hybrid clustering method that applied into the test area could easily detect similar land price zones with considerable accuracy levels, which are verified with some test statistics and real comparative standard land parcels done by manually.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.13 no.4
• /
• pp.480-485
• /
• 2003

We Propose a Path planning method to reduce the Inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2002.11a
• /
• pp.370-376
• /
• 2002

인터넷 환경에서 발생되는 수많은 데이터를 지능적으로 처리할 수 있는 자동화된 분석 시스템의 필요성이 제기된다. 이러한 시스템의 데이터 분석은 크게 지도 학습과 자율 학습으로 나된다. 본 논문에서는 특히 자율학습 군집화에 대한 자동화된 시스템으로서 지능화된 데이터 마이닝 에이전트를 제안한다. 군집화 과정에서는 데이터를 분석하는 분석가가 군집화의 방법과 결과 해석에 실시간으로 관여하기 어렵기 때문에 이러한 작업을 담당하는 지능화된 에이전트가 자동화된 군집화를 담당하면 효과적인 군집화 전략이 될 수 있다. 본 논문의 자동 군집화를 위한 지능화된 데이터 마이닝 에이전트 시스템은 군집화 수행 에이전트와 군집화 성능 평가 에이전트로 구성된 다중 에이전트로서 두 개의 에이전트가 서로 정보를 교환하면서 최적의 군집화를 수행한다. UCI Machine Repository 데이터를 이용한 실험을 통해 제안 시스템의 성능 평가를 수행하였다.