• Title/Summary/Keyword: TREC

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Improvement of the Short-Range Rainfall Forecasting Model using Wind Fields (바람장을 이용한 단시간 강우 예보모형 개선)

  • Kim, Gwang-Seob;Han, Kun-Yeun;Kim, Jong-Pil
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.1470-1473
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    • 2006
  • 연속된 두 장의 레이더 반사도(합성 CAPPI)를 이용하여 설정된 두 윈도우 사이의 최대 상관계수를 찾아 냄으로써 강수의 움직임을 파악하는 기존의 TREC(Tracking Radar Echoes by Correlation) 기법은 단지 통계적인 상관법을 이용하여 산출된 TREC 벡터를 외삽하기 때문에 강우 시스템의 이동양상을 물리적으로 표현하는데 한계를 가질 뿐만 아니라 강수가 직선운동을 하는 것처럼 묘사될 수밖에 없는 기법의 한계성을지니고 있다. 본 연구에서는 도플러 레이더로부터 생산되는 시선속도를 이용하여 바람장을 산출하고 이를 TREC 벡터와 연계시켜 단시간 예보모형을 개선하고자 하였다. 시선속도는 레이더로부터 멀어지거나 다가오는 물체의 속도성분이며, 이를 이용하여 강수 영역 내의 바람장을 산출할 수 있다. 이러한 바람장 정보와 연계한 TREC 벡터의 개선은 단시간 강우 예보모형의 개선을 통하여 짧은 시간에 급격한 발달하는 집중호우 등에 대한 보다 정확한 예보를 가능하게 한다.

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A BM25 based Passage Retrieval System for Developing an Efficient Question and Answering System (효율적인 질의응답시스템 개발을 위한 BM25기반의 단락 검색 시스템)

  • Lim, Heui Seok;Lee, Yong Shin;Rim, Hae Chang
    • The Journal of Korean Association of Computer Education
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    • v.6 no.4
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    • pp.23-30
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    • 2003
  • This paper proposes a passage retrieval system based on Okapi's BM25 for developing an efficient QA system and evaluates performances of the passage retrieval system. The test collection of TREC Q&A track which is composed of about one million documents was indexed and a hundred queries of TREC Q&A track are used as testing queries. The experimental results shows that the proposed passage retrieval system can reach to 100% recall rate by searching in only 1700 sentences while the conventional document retrieval system have to search about 120 thousands sentences which are about 70 times more than the proposed passage retrieval system.

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Improvement of Short-range Rainfall Forecasting Model using Multi-layer CAPPIs (다중 레이어 CAPPI를 이용한 단시간 강우 예보모형 개선)

  • Kim, Gwang-Seob;Han, Kun-Yeun;Kim, Jong-Pil
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.623-626
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    • 2006
  • 일정한 시간간격으로 제공되는 연속된 두 장의 레이더 반사도(합성 CAPPI) 자료의 최대 상관계수를 찾아 냄으로써 강수의 움직임을 산출하는 TREC(Tracking Radar Echoes by Correlation) 기법은 동일 고도의 레이더 반사도 자료를 이용하기 때문에 수평방향의 2차원이며, 대류성 구름체계에서 발생되는 수직 활동을 표현할 수 없는 한계성을 지니고 있다. 본 연구에서는 여러 고도의 레이더 반사도 자료를 이용하여 기존의 TREC 기법을 이용한 단시간 예보모형을 개선하고자 하였다. 특정고도의 레이더 반사도를 이용하여 에코를 추적하는 TREC 기법의 단점을 보완하기 위하여 서로 다른 고도의 레이더 반사도를 이용함으로써 기존의 접근법보다 실제 강수의 움직임에 더욱 가깝도록 단시간 강우 예보 정확도를 개선하였다.

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An Experimental Study on Topic Distillation Using Web Site Structure (웹 사이트 구조를 이용한 토픽 검색 연구)

  • Lee, Jee-Suk;Chung, Yung-Mee
    • Journal of the Korean Society for information Management
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    • v.24 no.3
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    • pp.201-218
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    • 2007
  • This study proposes a topic distillation algorithm that ranks the relevant sites selected from retrieved web pages, and evaluates the performance of the algorithm. The algorithm calculates the topic score of a site using its hierarchical structure. The TREC .GOV test collection and a set of TREC-2004 queries for topic distillation task are used for the experiment. The experimental results showed the algorithm returned at least 2 relevant sites in top ten retrieval results. We peformed an in-depth analysis of the relevant sites list provided by TREC-2004 to find out that the definition of topic distillation was not strictly applied in selecting relevant sites. When we re-evaluated the retrieved sites/sub-sites using the revised list of relevant sites, the performance of the proposed algorithm was improved significantly.

A Study on the Characteristics of Opinion Retrieval Using Term Statistical Analysis in Opinion Documents (의견 문서의 단어 통계 분석을 통한 의견 검색 특성에 관한 연구)

  • Han, Kyoung-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.21-29
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    • 2010
  • Opinion retrieval which searches the opinions expressed in documents by users cannot outperform significantly yet traditional topical retrieval which searches the facts. Therefore, the focus of this paper is to identify the statistical characteristics which can be applied to opinion retrieval by comparing and analyzing the term statistics of opinion and non-opinion documents in the blog domain. The TREC Blogs06 collection and 150 TREC topics are used in the experiments. The difference between term probability distributions in opinion documents is measured by JS divergence, and the difference according to the topic types and topic domains is also investigated. Moreover, the term probabilities of opinion terms are analyzed comparatively. The main findings of this study include the following: it is necessary to consider the topic-specific characteristics for the opinion detection; it is effective to extract positive and negative opinion terms according to the topics; the topic types are complementary to the topic domains; and special attention has to be given to the usage of the positive opinion terms.

Biorthogonal Wavelets-based Landsat 7 Image Fusion

  • Choi, Myung-Jin;Kim, Moon-Gyu;Kim, Tae-Jung;Kim, Rae-Young
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.724-726
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    • 2003
  • Currently available image fusion methods are not efficient for fusing the Landsat 7 images. Significant color distortion is one of the major problems. In this paper, using the well-known wavelet based method for data fusion between high-resolution panchromatic and low-resolution multispectral satellite images, we performed Landsat 7 image fusion. Based on the experimental results obtained from this study, we analyzed some reasons for color distortion. A new approach using the biorthogonal wavelets based method for data fusion is presented. This new method has reached an optimum fusion result - with the same spectral resolution as the multispectral image and the same spatial resolution as the panchromatic image with minimum artifacts.

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The First Newborn Screening Study of T-Cell Receptor Excision Circle and κ-Deleting Recombination Excision Circle for Severe Combined Immunodeficiency in Korea: A Pilot Study (국내 최초 T-Cell Receptor Excision Circle과 κ-Deleting Recombination Excision Circle 신생아 선별검사에 관한 연구)

  • Son, Sohee;Kang, Ji-Man;Kim, Jong Min;Sung, Sein;Kim, Yi-Seoul;Lee, Haejeong;Kim, BitA Reum;Lee, Yeon Kyoung;Ko, Sun Young;Shin, Son Moon;Kim, Yae-Jean
    • Pediatric Infection and Vaccine
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    • v.24 no.3
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    • pp.134-140
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    • 2017
  • Purpose: Severe combined immunodeficiency (SCID) is the most serious form of primary immunodeficiency. Infants with SCID are susceptible to life-threatening infections. To establish newborn screening for SCID in Korea, we performed a screening test for T-cell receptor excision circle (TREC) and ${\kappa}$-deleting recombination excision circle (KREC) in neonates and investigated the awareness of SCID among their parents. Methods: Collections of dried blood spots from neonates and parent surveys were performed at the Samsung Medical Center and Cheil General Hospital & Women's Healthcare Center in Korea. The amplification crossing point (Cp) value <37.0 was defined as TREC/KRECpositive based on cutoff values from measuring multiplex real-time polymerase chain reaction. A Cp value >39.0 was defined as negative. Results: For TREC/KREC screening, 141 neonates were enrolled; 63 (44.7%) were male. One hundred forty neonates (99.3%) had positive TREC/KREC results at the time of the initial test; 82.3% and 75.9% were positive and 17.0% and 23.4% were weakly positive for TREC and KREC, respectively. In one neonate (0.7%), the initial TREC/KREC test result was negative. However, repeated tests obtained and confirmed a positive result. For an awareness survey, 168 parents were engaged. Only 2% of parents (3/168) knew that the newborn screening test for SCID had been introduced and performed in other countries. Eighty-four percent of parents (141/168) replied that nationwide newborn SCID screening should be performed in Korean newborns. Conclusions: In this study, newborn SCID screening was performed along with assessment of public awareness of the SCID test in Korea. The study results showed that newborn SCID screening can be readily applied for clinical use at a relatively low cost in Korea.

Text Filtering using Iterative Boosting Algorithms (반복적 부스팅 학습을 이용한 문서 여과)

  • Hahn, Sang-Youn;Zang, Byoung-Tak
    • Journal of KIISE:Software and Applications
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    • v.29 no.4
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    • pp.270-277
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    • 2002
  • Text filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. The aim of this paper is to improve the accuracy of text filtering systems by using machine learning techniques. We apply AdaBoost algorithms to the filtering task. An AdaBoost algorithm generates and combines a series of simple hypotheses. Each of the hypotheses decides the relevance of a document to a topic on the basis of whether or not the document includes a certain word. We begin with an existing AdaBoost algorithm which uses weak hypotheses with their output of 1 or -1. Then we extend the algorithm to use weak hypotheses with real-valued outputs which was proposed recently to improve error reduction rates and final filtering performance. Next, we attempt to achieve further improvement in the AdaBoost's performance by first setting weights randomly according to the continuous Poisson distribution, executing AdaBoost, repeating these steps several times, and then combining all the hypotheses learned. This has the effect of mitigating the ovefitting problem which may occur when learning from a small number of data. Experiments have been performed on the real document collections used in TREC-8, a well-established text retrieval contest. This dataset includes Financial Times articles from 1992 to 1994. The experimental results show that AdaBoost with real-valued hypotheses outperforms AdaBoost with binary-valued hypotheses, and that AdaBoost iterated with random weights further improves filtering accuracy. Comparison results of all the participants of the TREC-8 filtering task are also provided.

Text Classification By Boosting Nave Bayes (베이지안 부스팅학습에 의한 문서 분류)

  • 김유환;장병탁
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.256-258
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    • 2000
  • 최근 들어, 여러 기계학습 알고리즘이 문서 분류와 여과에 사용되고 있다. 특히 AdaBoost와 같은 부스팅 알고리즘은 실세계의 문서 데이터에 사용되었을 때 비교적 좋은 성능을 보이는 것으로 알려져 있다. 그러나 지금까지의 부스팅 알고리즘은 모두 단어의 존재 여부만을 가지고 판단하는 분류자를 기반으로 하고 있기 때문에 가중치 정보를 충분히 사용할 수 없다는 단점이 있다. 이 논문에서는 나이브 베이스를 사용한 부스팅 알고리즘은 단어의 가중치 정보를 효율적으로 사용할 수 있을 뿐 아니라. 확률적으로도 의미있는 신뢰도(confidence ratio)를 생성 할 수 있기 때문이다. TREC-7과 TREC-8의 정보 여과 트랙(filtering track)에 대해서 실험한 결과 좋은 성능을 보여주었다.

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Probabilistic Evidences for Korean Predicate Structures (한국어 서술어 구조의 확률적 정보)

  • Lee, Seung-W.;Han, Young-S.
    • Annual Conference on Human and Language Technology
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    • 2004.10d
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    • pp.145-150
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    • 2004
  • 본 논문에서는 질의 응답 시스템에서 정답 추출을 위해 사용되는 표층 텍스트 패턴을 장거리 의존 문제에도 적용 가능하도록 확장하는 방법을 제안한다. 기존의 패턴 추출 시스템들의 패턴을 구성하고 있는 단어들간의 연속성과 불연속성에 대한 정보를 나타내도록 패턴 형태를 확장함으로써 장거리 의존 문제를 해결한다. 본 논문에서 제안한 형태의 패턴을 TREC-10의 질의를 이용해서 웹 데이터로 실험하여 정확도와 TREC의 평가 기준인 MRR을 사용해서 기존 시스템들과 성능을 비교했다.

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