• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.321-322
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• 2006

In this paper, we propose a method that extracts invariant iris codes from user's iris pattern in order to apply these codes to a new cryptographic construct called fuzzy vault. The fuzzy vault, proposed by Juels and Sudan, has been used to manage cryptographic key safely by merging with biometrics. Generally, iris data has intra-variation of iris pattern according to sensed environmental changes, but cryptography requires correctness. Therefore, to combine iris data and fuzzy vault, we have to extract an invariant iris feature from iris pattern. In this paper, we obtain invariant iris codes by clustering iris features extracted by independent component analysis(ICA) transform. From experimental results, we proved that the iris codes extracted by our method are invariant to sensed environmental changes and can be used in fuzzy vault.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.125-134
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• 2002

This paper proposes a method for identifying temporal pattern clusters to predict events in time series. Instead of predicting future values of the time series, the proposed method forecasts specific events that may be arbitrarily defined by the user. The prediction is defined by an event characterization function, which is the target of prediction. The events are predicted when the time series belong to temporal pattern clusters. To identify the optimal temporal pattern clusters, fuzzy goal programming is formulated to combine multiple objectives and solved by an adaptive differential evolution technique that can overcome the sensitivity problem of control parameters in conventional differential evolution. To evaluate the prediction method, five test examples are considered. The adaptive differential evolution is also tested for twelve optimization problems.

• ETRI Journal
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• v.29 no.5
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• pp.700-702
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• 2007

We present a relevance feedback approach based on multi-class support vector machine (SVM) learning and cluster-merging which can significantly improve the retrieval performance in region-based image retrieval. Semantically relevant images may exhibit various visual characteristics and may be scattered in several classes in the feature space due to the semantic gap between low-level features and high-level semantics in the user's mind. To find the semantic classes through relevance feedback, the proposed method reduces the burden of completely re-clustering the classes at iterations and classifies multiple classes. Experimental results show that the proposed method is more effective and efficient than the two-class SVM and multi-class relevance feedback methods.

• Journal of Intelligence and Information Systems
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• v.4 no.2
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• pp.61-83
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• 1998

본 연구는 웹 에이전트에 있어서 가장 핵심적인 부분이라 할 수 있는 사용자 특성모델 구축방법을 개선하는데 목적을 두고 있다. 사용자 특성모델을 귀납적 기계학습 방식으로 자동 추출하기 위해서는 사용자가 관심을 가지는 분야별로 문서를 자동 분류하는 작업이 매우 중요하다 지금까지의 방식은 사람이 관심여부에 따라 문서를 수동적으로 분류해 왔으나, 문서의 양이 기하급수적으로 증가할 경우 처리할 수 있는 문서의 양에는 한계가 있을 수밖에 없다. 또한 수작업 문서분류 방식을 웹 에이전트에 그대로 적용하였을 경우 사용자가 일일이 문서를 분류해야한다는 번거로움으로 인해 웹 에이전트의 효용성이 반감될 것이다. 따라서 본 연구에서는 비감독 문서분류 알고리즘과 그것을 바탕으로 얻어진 문서분류정보를 후처리(Post-Processing)함으로써 보다 간결하고 정확한 문서분류 결과를 얻을 수 있는 구체적인 방법을 제공하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.323-325
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• 2018

본 논문은 몰입도와 생체신호 간의 상관관계를 분석하기 위한 데이터 수집 및 데이터 군집에 대한 연구이다. 스마트기기를 이용해 걸음 수, 심박 수, 수면깊이와 같은 생체 데이터수집과, 수집한 데이터를 토대로 사용자의 행동패턴을 분석한다. 사용자 생체 데이터를 k-means 클러스터링과 계층적 클러스터링을 혼합해 이용해 앞서 나열한 데이터와 사용자의 집중도와 연관관계분석이 최종 목표이다.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.137-142
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• 2019

This paper proposed bitmap based spatial data transmission scheme in need of rapid transmission through network in mobile environment that use and creation of data are frequently happen. Former researches that used clustering algorithms, focused on providing service using spatial data can cause delay since it doesn't consider the transmission speed. This paper guaranteed rapid service for user by convert spatial data to bit, leads to more transmission of bit of MTU, the maximum transmission unit. In the experiment, we compared arithmetically default data composed of 16 byte and spatial data converted to bitmap and for simulation, we created virtual data and compared its network transmission speed and conversion time. Virtual data created as standard normal distribution and skewed distribution to compare difference of reading time. The experiment showed that converted bitmap and network transmission are 2.5 and 8 times faster for each.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5203-5217
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• 2018

In order to increase the capacity and improve the spectrum efficiency of wireless communication systems, this paper proposes a rate-based two-sided many-to-one matching game algorithm for energy-harvesting small cells with non-orthogonal multiple access (NOMA) in heterogeneous cellular networks (HCN). First, we use a heuristic clustering based channel allocation algorithm to assign channels to small cells and manage the interference. Then, aiming at addressing the user access problem, this issue is modeled as a many-to-one matching game with the rate as its utility. Finally, considering externality in the matching game, we propose an algorithm that involves swap-matchings to find the optimal matching and to prove its stability. Simulation results show that this algorithm outperforms the comparing algorithm in efficiency and rate, in addition to improving the spectrum efficiency.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.579-582
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• 2007

최근 들어 더욱 UCC(User Created Contents)등과 같은 대용량 멀티미디어(multimedia) 서비스에 대한 요구가 나날이 증가되면서 부하분산에 중점을 둔 웹 클러스터링 시스템(Web Clustering System) 에서 기존의 작은 크기의 스트림 데이터(Stream Data)나 조금 더 다양한 데이터를 위한 읽기 성능을 대용량 데이터에 초점을 맞춘 방안으로 최적화 시키는 것이 중요시되고 있다. 본 논문에서는 대용량 멀티미디어를 중심으로 실제 서비스시 간과 되어질 수 있는 운영체제(Operating System, O/S)에서의 I/O 인식, 디스크 제어 프로그램에서의 I/O, 웹 클러스터의 부하분산정책의 파라미터(Parameter)를 개선함으로써 읽기성능 향상 방안을 제시한다.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.121-136
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• 2008

Although domestic research funding organizations require patented technologies as an outcome of financial aids, they have much difficulty in evaluating qualitative value of the patented technology due to lack of systematic methods. Especially, because citation data is not essential to patent application in Korea, it is very difficult to evaluate a patent using the incomplete citation data. This study proposes a method for evaluating technology importance of a patent when there is no or insufficient citation data in patents. The technology importance of a patent can be evaluated objectively and quantitatively by the proposed method which consists of 5 steps such as selection of a target patent, collection of related patents, preparation of key word vector, clustering patents, and technological importance assessment. The method was applied to a patent on 'user identification method for payment using mobile terminal' in order to evaluate technology importance and demonstrate how the method works.