• Title/Summary/Keyword: Case Retrieval

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Case-Based Retrieval System Construction (Case 기반 컴포넌트 검색 시스템 설계)

  • Kim, Gui-Jug
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.357-360
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    • 2005
  • 본 연구는 소스 코드를 재사용하기 위한 Case 기반 검색에 있어서 효율적인 검색 시스템을 구축하는 방법을 제안하고자 한다. 소스 코드의 객체지향적인 특성을 만족하기 위하여 각 노드 간 객체지향 상속의 개념을 표현할 수 있도록 초기 관련값을 시소러스로 구축하고자 한다. 이때, 각 Case를 구성하는 클래스들을 상속관계에 따라 개념적으로 분류하였고, 시소러스 방법에 퍼지 논리를 적용하여 객체지향 시소러스를 생성하여 의미망을 구축한다. 또한, 의미망의 노드와 간선을 활성화시키고 활성값을 전파시키기 위해 사용되는 spreading activation 방법의 단점을 보완하여 spreading activation의 성능은 최대한 유지하면서 검색 속도를 향상시킬 수 있는 방법을 제안하고자 한다.

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Prediction of KOSPI using Data Editing Techniques and Case-based Reasoning (자료편집기법과 사례기반추론을 이용한 한국종합주가지수 예측)

  • Kim, Kyoung-Jae
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.6
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    • pp.287-295
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    • 2007
  • This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

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Ship's Collision Avoidance Support System Using Fuzzy-CBR

  • Park, Gyei-Kark;Benedictos John Leslie RM.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.5
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    • pp.635-641
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    • 2006
  • Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and infer the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

Building of Collision Avoidance Algorithm based on CBR

  • Park Gyei-Kark;Benedictos John Leslie RM
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.39-44
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    • 2006
  • Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning(CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and index the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

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Design of Moving Picture Retrieval System using Scene Change Technique (장면 전환 기법을 이용한 동영상 검색 시스템 설계)

  • Kim, Jang-Hui;Kang, Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.3
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    • pp.8-15
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    • 2007
  • Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.

Dual Doppler Wind Retrieval Using a Three-dimensional Variational Method (3차원 변분법을 사용한 이중 도플러 바람장 분석)

  • Lee, SeonYong;Choi, Young-Jean;Chan, Dong-Eon
    • Atmosphere
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    • v.17 no.1
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    • pp.69-86
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    • 2007
  • The characteristics of the dual-Doppler wind retrieval method based on a three dimensional variational (3DVAR) conception were investigated from the following four points of view; the sensitivity of the number of iteration, the effect of the weak constraint term, the effect of the smoothness term, and the sensitivity of the error mixing ratio of the radial velocities. In the experiment, the radial velocities relative to the Gosan and Jindo radar sites of the Korea Meteorological Administration (KMA) were calculated from the forecasting of the WRF (Weather Research and Forecast; Skamarock, 2004) model at 1330 UTC 30 June 2006, which is the one and half hour forecast from the initial time, 1200 UTC on that day. The results showed that the retrieval performance of the horizontal wind field was robust, but that of the vertical wind was sensitive to the external conditions, such as iteration number and the on/off of the weak constraint term. The sensitivity of error mixing ratio was so large that even the horizontal wind retrieval efficiency was reduced a lot. But the sensitivity of the smooth term was not so large. When we applied this method to the real mesoscale convective system (MCS) between the Gosan and Jindo radar pair at 1430 UTC 30 June 2006, the wind structure of the convective cells in the MCS was consistently retrieved relative to the reflectivity factor structure. By comparing the vertical wind structure of this case with that of 10 minutes after, 1440 UTC 30 June 2006, we got the physical consistency of our method.

Web-based Image Retrieval and Classification System using Sketch Query (스케치 질의를 통한 웹기반 영상 검색과 분류 시스템)

  • 이상봉;고병철;변혜란
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.703-712
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    • 2003
  • With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.

Content-based Image Retrieval Using HSI Color Space and Neural Networks (HSI 컬러 공간과 신경망을 이용한 내용 기반 이미지 검색)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.5 no.2
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    • pp.152-157
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    • 2010
  • The development of computer and internet has introduced various types of media - such as, image, audio, video, and voice - to the traditional text-based information. However, most of the information retrieval systems are based only on text, which results in the absence of ability to use available information. By utilizing the available media, one can improve the performance of search system, which is commonly called content-based retrieval and content-based image retrieval system specifically tries to incorporate the analysis of images into search systems. In this paper, a content-based image retrieval system using HSI color space, ART2 algorithm, and SOM algorithm is introduced. First, images are analyzed in the HSI color space to generate several sets of features describing the images and an SOM algorithm is used to provide candidates of training features to a user. The features that are selected by a user are fed to the training part of a search system, which uses an ART2 algorithm. The proposed system can handle the case in which an image belongs to several groups and showed better performance than other systems.

Enhancement of HCB Tree for Improving Retrieval Performance and Dynamic Environments (검색 성능 향상과 동적 환경을 위한 HCB 트리의 개선)

  • Kim, Sung Wan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.2
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    • pp.365-371
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    • 2015
  • CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

Comparison of User-generated Tags with Subject Descriptors, Author Keywords, and Title Terms of Scholarly Journal Articles: A Case Study of Marine Science

  • Vaidya, Praveenkumar;Harinarayana, N.S.
    • Journal of Information Science Theory and Practice
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    • v.7 no.1
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    • pp.29-38
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    • 2019
  • Information retrieval is the challenge of the Web 2.0 world. The experiment of knowledge organisation in the context of abundant information available from various sources proves a major hurdle in obtaining information retrieval with greater precision and recall. The fast-changing landscape of information organisation through social networking sites at a personal level creates a world of opportunities for data scientists and also library professionals to assimilate the social data with expert created data. Thus, folksonomies or social tags play a vital role in information organisation and retrieval. The comparison of these user-created tags with expert-created index terms, author keywords and title words, will throw light on the differentiation between these sets of data. Such comparative studies show revelation of a new set of terms to enhance subject access and reflect the extent of similarity between user-generated tags and other set of terms. The CiteULike tags extracted from 5,150 scholarly journal articles in marine science were compared with corresponding Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title terms. The Jaccard similarity coefficient method was employed to compare the social tags with the above mentioned wordsets, and results proved the presence of user-generated keywords in Aquatic Science and Fisheries Abstracts descriptors, author keywords, and title words. While using information retrieval techniques like stemmer and lemmatization, the results were found to enhance keywords to subject access.