• Title/Summary/Keyword: information retrieval system

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Video Retrieval System supporting Content-based Retrieval and Scene-Query-By-Example Retrieval (비디오의 의미검색과 예제기반 장면검색을 위한 비디오 검색시스템)

  • Yoon, Mi-Hee;Cho, Dong-Uk
    • The KIPS Transactions:PartB
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    • v.9B no.1
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    • pp.105-112
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    • 2002
  • In order to process video data effectively, we need to save its content on database and a content-based retrieval method which processes various queries of all users is required. In this paper, we present VRS(Video Retrieval System) which provides similarity query, SQBE(Scene Query By Example) query, and content-based retrieval by combining the feature-based retrieval and the annotation-based retrieval. The SQBE query makes it possible for a user to retrieve scones more exactly by inserting and deleting objects based on a retrieved scene. We proposed query language and query processing algorithm for SQBE query, and carried out performance evaluation on similarity retrieval. The proposed system is implemented with Visual C++ and Oracle.

Image Retrieval using Spatial Information and Color Changing Ratio (공간정보와 색상변화율을 이용한 영상검색)

  • Kang, Ki-Hyun;Park, Yu-Sin;Yoon, Yong-In;Choi, Jong-Soo;Kim, Dong-Wook
    • Journal of Korea Multimedia Society
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    • v.11 no.1
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    • pp.23-33
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    • 2008
  • In this paper, we propose a image retrieval algorithm using spatial information and color changing ratio. The proposed method extracts color regions from images by threshold $\tau$ to extract spatial information. During this process, we count extracted color regions and color changing, and these values are used to obtain color changing ratio. Image similarity between images is measured by extracted spatial information. Additively, color changing ratio makes images that has similar color changing ratio to be more higher retrieval rank. In our experiment using various natural images, we demonstrate a proposed method shows better performance than other common retrieval methods using color informations.

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Learning Discriminative Fisher Kernel for Image Retrieval

  • Wang, Bin;Li, Xiong;Liu, Yuncai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.3
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    • pp.522-538
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    • 2013
  • Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

A Method for Information Source Selection using Teasaurus for Distributed Information Retrieval

  • Goto, Shoji;Ozono, Tadachika;Shintani, Toramatsu
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.272-277
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    • 2001
  • In this paper, we describe a new method for selecting information sources in a distributed environment. Recently, there has been much research on distributed information retrieval, that is information retrieval (IR) based on a multi-database model in which the existence of multiple sources is modeled explicitly. In distributed IR, a method is needed that would enable selecting appropriate sources for users\` queries. Most existing methods use statistical data such as document frequency. These methods may select inappropriate ate sources if a query contains polysemous words. In this paper, we describe an information-source selection method using two types of thesaurus. One is a thesaurus automatically constructed from documents in a source. The other is a hand-crafted general-purpose thesaurus(e.g. WordNet). Terms used in documents in a source differ from one another and the meanings of a term differ depending on th situation in which the term is used. The difference is a characteristic of the source. In our method, the meanings of a term are distinguished between by the relationship between the term and other terms, and the relationship appear in the co-occurrence-based thesaurus. In this paper, we describe an algorithm for evaluating a usefulness of a source for a query based on a thesaurus. For a practical application of our method, we have developed Papits, a multi-agent-based in formation sharing system. An experiment of selection shows that our method is effective for selecting appropriate sources.

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Query-by-emotion sketch for local emotion-based image retrieval (지역 감성기반 영상 검색을 위한 감성 스케치 질의)

  • Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
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    • v.10 no.6
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    • pp.113-121
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    • 2009
  • In order to retrieve images with different emotions in regions of the images, this paper proposes the image retrieval system using emotion sketch. The proposed retrieval system divides an image into $17{\times}17$ sub-regions and extracts emotion features in each sub-region. In order to extract the emotion features, this paper uses emotion colors on 160 emotion words from H. Nagumo's color scheme imaging chart. We calculate a histogram of each sub-region and consider one emotion word having the maximal value as a representative emotion word of the sub-region. The system demonstrates the effectiveness of the proposed emotion sketch and our experimental results show that the system successfully retrieves on the Corel image database.

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Design of a hypermedia system for effective searching and browsing (탐색과 브라우징을 지원하는 하이퍼미디어 시스템의 설계)

  • 고영곤;최윤철
    • Journal of the Korean Society for information Management
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    • v.10 no.1
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    • pp.15-30
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    • 1993
  • Hypermedia system supports associative linking concept for multimedia information using link and node concept, and overcomes the limitations of database system and text retrieval system in some application areas. This study shows the design and implementation of a hypermedia system which supports text, graphics, image and voice /sound information. This system has been designed to integrate the browsing and searching functions of the hypermedia system for efficient multimedia information retrieval and user-interface. To demonstrate the function and capability of the system, an application was made in the area of Bible and related information.

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ECoMOT : An Efficient Content-based Multimedia Information Retrieval System Using Moving Objects' Trajectories in Video Data (ECoMOT : 비디오 데이터내의 이동체의 제적을 이용한 효율적인 내용 기반 멀티미디어 정보검색 시스템)

  • Shim Choon-Bo;Chang Jae-Woo;Shin Yong-Won;Park Byung-Rae
    • The KIPS Transactions:PartB
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    • v.12B no.1 s.97
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    • pp.47-56
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    • 2005
  • A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

The Information System of Science Technology and the Infrastructure of Information Technology in North Korea (북한의 정보화 기반과 과학기술정보시스템)

  • 송승섭
    • Journal of Korean Library and Information Science Society
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    • v.33 no.1
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    • pp.99-120
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    • 2002
  • This study is to firstly investigate information infrastructure in North Korea such as communication network, hardware, software and etc, and then, based on it, to grasp the present condition of information technology in libraries there. Also, it is to analyze the information system of science technology in order to research the circulation system of science information with focusing on the Central Science Technology Intelligence (CSTI), a representative intelligence agency for science technology in North Korea, and on the retrieval program of “KWANGMYOUNG System”developed by CSTI and used broadly.

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Content based image retrieval using maximum color

  • Park, Jong-An
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.6 no.4
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    • pp.232-237
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    • 2013
  • This paper presents image database retrieval based on maximum color occurrenceusing Hue, Saturation and Value (HSV) color space. Our system is based on color segmentation. We dividedthe image into n number of areas based on different selected ranges of hue and value, then each area is partitioned into m number of segments based on the number of pixels it contains, after this we calculated the maximumcolor occurrence in each segment and used its HSV value. This is used as a feature vector.

Medical Image Retrieval based on Multi-class SVM and Correlated Categories Vector

  • Park, Ki-Hee;Ko, Byoung-Chul;Nam, Jae-Yeal
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.8C
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    • pp.772-781
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    • 2009
  • This paper proposes a novel algorithm for the efficient classification and retrieval of medical images. After color and edge features are extracted from medical images, these two feature vectors are then applied to a multi-class Support Vector Machine, to give membership vectors. Thereafter, the two membership vectors are combined into an ensemble feature vector. Also, to reduce the search time, Correlated Categories Vector is proposed for similarity matching. The experimental results show that the proposed system improves the retrieval performance when compared to other methods.