• Proceedings of the Korea Multimedia Society Conference
• /
• 2001.11a
• /
• pp.423-428
• /
• 2001

유전 알고리즘을 이용한 정보 필터링 에이전트는 기존의 검색엔진에서 찾고자 하는 문서에 대해 검색된 문서의 유사도가 낮은 문제점을 해결한다. 본 논문에서는 HTML 태그의 중요도 가중치와 HTML 태그 안의 위치에 대한 가중치를 유전 알고리즘을 이용하여 학습한다. 여기서 학습된 가중치가 높은 태그와 태그 안의 위치 그리고 출현하는 빈도수에 대한 중요도 가중치를 다시 유전 알고리즘을 이용하여 학습하고 여기서 학습된 가중치로 검색된 문서를 필터링하여 정보 검색 성능을 향상시킬 수 있는 방법을 제안한다. 이 때 태그의 중요도 가중치 값을 학습하는 방법으로 하나의 태그를 유전자로 매핑하고 일련의 태그 집합을 염색체로 표현한 유전 알고리즘을 이용한다. 태그 안의 위치에 대한 중요도 가중치 값도 같은 방법을 이용한다. 여기서 나온 태그와 위치 그리고 빈도 수에 대한 중요도 가중치 값을 다시 유전자 알고리즘 이용하여 계산하다. 이 값으로 검색된 문서를 필터링하여 기존의 정보검색보다 검색자가 원하는 검색문서에 상당한 정확율을 제공하는 방법을 제안한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.432-434
• /
• 2008

This paper deals with the DTW algorithm for the filtering contents, in order to improve the filtering performance rate. Contents filtering is the technology that confirm the identification of contents by using the feature of voice. Such technique is classified into general contents and adults contents. This proposed method extracts the information of voice contribute to improvement of filtering contents. In other words, We proposed filtering identification rate can be improved by using DTW algorithm. As a result, the proposed method is utilized improvement of filtering contents. Finally, we provide contents examples to test the accuracy of the proposed feature. Consequently, We know that the difference of characteristic between general contents and adults contents. In the future, We utilize this to improve filtering performance rate.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2009.11a
• /
• pp.441-442
• /
• 2009

RFID 시스템의 적용범위가 증가함에 따라 실시간으로 처리해야 하는 태그의 정보도 급격하게 증가하고 있다. 따라서 불필요한 태그정보를 제거하고 정제하여 클라이언트로 전달하는 RFID 미들웨어의 역할이 증가하고 있다. 미들웨어에서 태그정보를 필터링 하기 위한 Brute force 방법은 대용량의 태그정보의 필터링에는 비효율적이며 미들웨어의 성능을 저하시키는 원인이 된다. 본 논문은 빠른 시간에 효과적인 필터링을 위해 미들웨어 표준인 EPCglobal ALE의 ECSpec에 정의된 필터 패턴들 사이의 연관 관계를 구성하여 패턴의 비교 횟수를 감소시키고, 표준에서 정의한 EPC 태그형식의 특징을 해싱 알고리즘에 적용하여 빠른 검색을 수행함으로써 효율적인 RFID 미들웨어의 필터링 알고리즘을 구현하였다.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.131-134
• /
• 2006

LiDAR(Light Detection And Ranging) 데이터 처리에 있어서 건물, 자동차, 수목 등의 비지면 객체와 지면을 분류하는 필터링 과정은 DEM(Digital Elevation Model) 구축을 위해서 중요하다. 도심지역의 건물추출 등의 필터링에 관한 연구는 활발히 진행되고 있으나 국내의 경우 수목에 대한 필터링은 비교적 연구가 미흡하였다. 따라서 이 연구에서는 기존에 다루어진 몇 가지 알고리즘을 분석하고 산림지역에 활용해 봄으로써 각 필터링에 관한 장단점을 비교하였다.

• KIISE Transactions on Computing Practices
• /
• v.23 no.1
• /
• pp.57-64
• /
• 2017

Short message service (SMS) is one of the most important communication methods for people who use mobile phones. However, illegal advertising spam messages exploit people because they can be used without the need for friend registration. Recently, spam message filtering systems that use machine learning have been developed, but they have some disadvantages such as requiring many calculations. In this paper, we implemented a spam message filtering system using the set-based POI search algorithm and sentence similarity without servers. This algorithm can judge whether the input query is a spam message or not using only letter composition without any server computing. Therefore, we can filter the spam message although the input text message has been intentionally modified. We added a specific preprocessing option which aims to enable spam filtering. Based on the experimental results, we observe that our spam message filtering system shows better performance than the original set-based POI search algorithm. We evaluate the proposed system through extensive simulation. According to the simulation results, the proposed system can filter the text message and show high accuracy performance against the text message which cannot be filtered by the 3 major telecom companies.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10a
• /
• pp.473-476
• /
• 2000

최근 전자상거래에서 에이전트 기술들이 많이 나타나고 있는데, 주목해야 할 것은 패키지 형태로 내장될 수 있는 에이전트이다. 전자상거래 솔루션에 탑재되어 자동화시킨 에이전트로서 NetPerception 의 GroupLens 엔진과 MacroMedia의 LikeMinds가 있는데 이들은 협동적 필터링을 구현한 것들이다. 현재 이러한 협동적 필터링 에이전트 시스템이 탑재된 전자상거래 솔루션들이 등장하고 있다. 하지만 add-on 성격이 부족하고, 실제 협동적 필터링 알고리즘에 의해 고객의 취향이나 기호에 맞는 아이템을 추천하는 진정한 의미의 에이전트 시스템은 찾아보기 힘들다. 그래서, 이러한 점을 보완한 MindReader 시스템을 개발하였다. 제안된 알고리즘은 기존의 GroupLens 알고리즘에 클러스터링을 접목시킨 알고리즘을 사용하였다.

• Information Systems Review
• /
• v.9 no.1
• /
• pp.85-103
• /
• 2007

The purpose of this study is to evaluate the performance of collaborative filtering recommender algorithms for better prediction accuracy of the customer's preference. The accuracy of customer's preference prediction is compared through the MAE of neighborhood based collaborative filtering algorithm and correspondence mean algorithm. It is analyzed by using MovieLens 1 Million dataset in order to experiment with the prediction accuracy of the algorithms. For similarity, weight used in both algorithms, commonly, Pearson's correlation coefficient and vector similarity which are used generally were utilized, and as a result of analysis, we show that the accuracy of the customer's preference prediction of correspondence mean algorithm is superior. Pearson's correlation coefficient and vector similarity used in two algorithms are calculated using the preference rating of two customers' co-rated movies, and it shows that similarity weight is overestimated, where the number of co-rated movies is small. Therefore, it is intended to increase the accuracy of customer's preference prediction through expanding the number of the existing co-rated movies.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.11
• /
• pp.2715-2720
• /
• 2014

Median filtering is very effective to remove impulse type noises, so it has been widely used in many signal processing applications. However, due to the time complexity of its non-linearity, median filtering is often used using a small filter window size. A lot of work has been done on devising fast median filtering algorithms, but most of them can be efficiently applied to input data with finite integer values like images. Little work has been carried out on fast 2-d median filtering algorithms that can deal with real-valued 2-d data. In this paper, a fast and simple median 2-d filter is presented, and its performance is compared with the Matlab's 2-d median filter and a heap-based 2-d median filter. The proposed algorithm is shown to be much faster than the Matlab's 2-d median filter and consistently faster than the heap-based algorithm that is much more complicated than the proposed one. Also, a more efficient median filtering scheme for 2-d real valued data with a finite range of values is presented that uses higher-bit integer 2-d median filtering with negligible quantization errors.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.30 no.1
• /
• pp.39-48
• /
• 2012

Filtering process that separates ground and non-ground points from LIDAR data is important in order to create the digital elevation model (DEM) or extract objects on the ground. The purpose of this research is to select the most effective filtering algorithm through qualitative and quantitative analysis for the existing filtering method used to extract ground points from LIDAR data. For this, four filtering methods including Adaptive TIN(ATIN), Perspective Center-based filtering method(PC), Elevation Threshold with Expand Window(ETEW) and Progressive Morphology(PM) were applied to mountain area, urban area and the area where building and mountains exist together. Then the characteristics for each method were analyzed. For the qualitative comparison of four filtering methods used for the research, visual method was applied after creating shaded relief image. For the quantitative comparison, an absolute comparison was conducted by using control points observed by GPS and a relative comparison was conducted by the digital elevation model of the National Geographic Information Institute. Through the filtering experiment of the LIDAR data, the Adaptive TIN algorithm extracted the ground points in mountain area and urban area most effectively. In the area where buildings and mountains coexist, progressive morphology algorithm generated the best result. In addition, as a result of qualitative and quantitative comparisons, the applicable filtering algorithm regardless of topographic characteristics appeared to be ATIN algorithm.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.12
• /
• pp.43-48
• /
• 2011

Among various methods proposed earlier, fuzzy image filtering is usually one of the favored techniques because it has less blurring effect and the decrease of noise removal rate after filtering. However, fuzzy filtering is ineffective on color images since it is firstly developed with gray scale. Thus, in this paper, we propose a fuzzy filtering algorithm for color images. First, we divide RGB color information from image into three channels of R, G, and B and judge the possibility of each pixel with mask by fuzzy logic independently. The output pixel value might be the average or median according to the degree of noise. Our experiment successfully verifies the effectiveness of new algorithm in color image.