• Title/Summary/Keyword: Retrieval Efficiency

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Weighting of XML Tag using User's Query (사용자 질의를 이용한 XML 태그의 가중치 결정)

  • Woo Seon-Mi;Yoo Chun-Sik;Kim Yong-Sung
    • The KIPS Transactions:PartD
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    • v.12D no.3 s.99
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    • pp.439-446
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    • 2005
  • XML is the standard that can manage systematically WWW documents and increase retrieval efficiency. Because XML documents have the information of contents and that of structure in single document, users can get more suitable retrieval result by retrieving the information of content as well as that of logical structure. In this paper, we will propose a method to calculate the weights of XML tags so that the information of XML tag is used to index decision. A proposed method creates term vector and weight vector for XML tags, and calculates weight of tag by reflecting user's retrieval behavior (user's query). And it decides the weights of index terms of XML document by reflecting the weights of tags. And we will perform an evaluation of proposed method by comparison with existing researches using weights of paragraphs.

Improvement of Retrieval Performance using Automatically Weighted Image Features (영상 특징들에 자동 가중치 부여를 이용한 검색 성능 개선)

  • Kim, Kang-Wook;Park, Jong-Ho;Hwang, Chang-Sik
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.6
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    • pp.17-21
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    • 2000
  • Typical image features such as color, shape, and texture are used in content based image retrieved. Retrieval which uses only one image feature has little performance in case that the content of image is complex or database contains many images. So, many approaches for integrating these features have been studied. However, the problem of these approaches is how to appropriately weight the image features at query time. In this paper, we propose a new retrieval method using automatically weighted image features. We perform computer simulations in test database which consists of various kinds of images. The experimental results show that the proposed method has better performance than previous works, which use fixed weight for each feature mostly, in respect to several performance cvaluations such as precision vs recall, retrieval efficiency, and ranking measure.

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Investigating the End-User Tagging Behavior and its Implications in Flickr (플리커 이미지 자료에 대한 이용자 태깅 행태 분석과 활용 방안)

  • Kim, Hyun-Hee;Kim, Min-Kyung
    • Journal of Information Management
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    • v.40 no.2
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    • pp.71-94
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    • 2009
  • Indexing images using traditional indexing methods like taxonomy is not always efficient because of its visual content. This study examined how to apply folksonomies to image retrieval. To do this, first, we developed a category model for image tags found in Flickr. The model includes five categories and seventeen subcategories. Second, in order to evaluate the usefulness of the model to represent the various image tags as well as to investigate the end-user tagging behavior, three researchers classified the sampled image tags(141 most popular tags, 105 tags on three individual tag clouds and 3,848 image tags assigned on 156 images) according to the model. Finally, based on the research results, we proposed three methods for efficient image retrieval: extending folksonomies by combining them with ontologies; improving image retrieval efficiency using visual content and folksonomies; and updating taxonomy using folksonomies.

Image Information Retrieval Using DTW(Dynamic Time Warping) (DTW(Dynamic Time Warping)를 이용한 영상 정보 검색)

  • Ha, Jeong-Yo;Lee, Na-Young;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of Digital Contents Society
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    • v.10 no.3
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    • pp.423-431
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    • 2009
  • There are various image retrieval methods using shape, color and texture features. One of the most active area is using shape and color information. A number of shape representations have been suggested to recognize shapes even under affine transformation. There are many kinds of method for shape recognition, the well-known method is Fourier descriptors and moment invariant. The other method is CSS(Curvature Scale Space). The maxima of curvature scale space image have already been used to represent 2-D shapes in different applications. Because preexistence CSS exists several problems, in this paper we use improved CSS method for retrieval image. There are two kinds of method, One is using RGB color information feature and the other is using HSI color information feature. In this paper we used HSI color model to represent color histogram before, then use it as comparison measure. The similarity is measured by using Euclidean distance and for reduce search time and accuracy, We use DTW for measure similarity. Compare with the result of using Euclidean distance, we can find efficiency elevated.

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Content and Trajectory Retrievals of Moving Objects in Video Databases (비디오 데이타베이스에서 이동 객체의 내용 및 궤적 검색)

  • 복경수;유재수
    • Journal of KIISE:Databases
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    • v.31 no.3
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    • pp.219-231
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    • 2004
  • Recently, together with increasing use of multimedia data, many works on moving objects in video databases have been made. Moving objects change visual features and spatial positions with the lapse of time in video data. And they arc related to the other objects or events. In this paper, we propose a new modeling and various query types of moving objects for content based retrieval in video databases. The proposed modeling represents visual features, moving trajectories and semantic contents related to objects. Therefore, it allows to process various query types. And we propose various query operators for the retrieval types. To show the superiority of our modoling, we implement the retrieval systems and compare it with the existing methods in terms of the supporting query types. The proposed method supports various query types and improves the efficiency of the query processing over the existing methods.

Interactivity within large-scale brain network recruited for retrieval of temporally organized events (시간적 일화기억인출에 관여하는 뇌기능연결성 연구)

  • Nah, Yoonjin;Lee, Jonghyun;Han, Sanghoon
    • Korean Journal of Cognitive Science
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    • v.29 no.3
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    • pp.161-192
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    • 2018
  • Retrieving temporal information of encoded events is one of the core control processes in episodic memory. Despite much prior neuroimaging research on episodic retrieval, little is known about how large-scale connectivity patterns are involved in the retrieval of sequentially organized episodes. Task-related functional connectivity multivariate pattern analysis was used to distinguish the different sequential retrieval. In this study, participants performed temporal episodic memory tasks in which they were required to retrieve the encoded items in either the forward or backward direction. While separately parsed local networks did not yield substantial efficiency in classification performance, the large-scale patterns of interactivity across the cortical and sub-cortical brain regions implicated in both the cognitive control of memory and goal-directed cognitive processes encompassing lateral and medial prefrontal regions, inferior parietal lobules, middle temporal gyrus, and caudate yielded high discriminative power in classification of temporal retrieval processes. These findings demonstrate that mnemonic control processes across cortical and subcortical regions are recruited to re-experience temporally-linked series of memoranda in episodic memory and are mirrored in the qualitatively distinct global network patterns of functional connectivity.

A Study of a Server Selection Model for Selecting a Replicated Server based on Downstream Measurement in the Server-side

  • Kim, Seung-Hae;Lee, Won-Hyuk;Cho, Gi-Hwan
    • Journal of Information Processing Systems
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    • v.2 no.2
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    • pp.130-134
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    • 2006
  • In the distributed replicating server model, the provision of replicated services will improve the performance of the providing service and efficiency for clients. Efficiently composing the server selection algorithm decreases the retrieval time for replicated data. In this paper, we define the system model that selects and connects the replicated server that provides an optimal service using the server-side downstream measurement and propose a server selection algorithm.

Predicates Indexing for efficiency improvement in Korean Information Retrieval System (한국어 정보검색 시스템의 성능 향상을 위한 용언 색인)

  • 박진희;박대원;박민식;남현숙;김광영;권혁철
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10b
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    • pp.164-166
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    • 2000
  • 지금까지 대부분의 정보검색 시스템은 명사만을 색인어로 추출하여 사용하였다. 명사는 문서를 대표할 수 있는 어휘 요소이다. 그러나 명사 색인어만 가지고는 문서의 주제를 정확하게 나타낼 수 없다. 본 논문은 명사 색인어와 함께 용언도 색인어로 추출하여 사용하는 한국어 정보 검색시스템을 제시한다. 또한, 용역 색인어와 명사 색인어의 상대적 가중치를 검색에 이용하여 사용자의 질의에 적합한 문서를 검색할 수 있도록 한다. 이러한 과정에서 발견된 문제점은 향후 연구 과제로 계속 향상시켜나갈 것이다.

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Alleviating Semantic Term Mismatches in Korean Information Retrieval (한국어 정보 검색에서 의미적 용어 불일치 완화 방안)

  • Yun, Bo-Hyun;Park, Sung-Jin;Kang, Hyun-Kyu
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.12
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    • pp.3874-3884
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    • 2000
  • An information retrieval system has to retrieve all and only documents which are relevant to a user query, even if index terms and query terms are not matched exactly. However, term mismatches between index terms and qucry terms have been a serious obstacle to the enhancement of retrieval performance. In this paper, we discuss automatic term normalization between words in text corpora and their application to a Korean information retrieval system. We perform two types of term normalizations to alleviate semantic term mismatches: equivalence class and co-occurrence cluster. First, transliterations, spelling errors, and synonyms are normalized into equivalence classes bv using contextual similarity. Second, context-based terms are normalized by using a combination of mutual information and word context to establish word similarities. Next, unsupervised clustering is done by using K-means algorithm and co-occurrence clusters are identified. In this paper, these normalized term products are used in the query expansion to alleviate semantic tem1 mismatches. In other words, we utilize two kinds of tcrm normalizations, equivalence class and co-occurrence cluster, to expand user's queries with new tcrms, in an attempt to make user's queries more comprehensive (adding transliterations) or more specific (adding spc'Cializationsl. For query expansion, we employ two complementary methods: term suggestion and term relevance feedback. The experimental results show that our proposed system can alleviatl' semantic term mismatches and can also provide the appropriate similarity measurements. As a result, we know that our system can improve the rctrieval efficiency of the information retrieval system.

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Implementing the Faceted Navigation Interface for Searching Performing Arts Contents (공연예술 콘텐츠 검색을 위한 패싯 내비게이션 인터페이스 구현)

  • Lee, Won-Kyung;Seo, Eun-Gyoung
    • Journal of the Korean Society for information Management
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    • v.33 no.2
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    • pp.77-102
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    • 2016
  • The effective searching for performing arts contents can be achieved by providing various access points and searching methods based on specialized metadata. The purpose of this study is to develop a faceted navigation interface which user could effectively and efficiently retrieve performing arts contents even if the users do not know accurate descriptive information about them. Therefore, the study, first, investigated search access points and navigation items providing by other the performing arts retrieval systems and to analyze information seeking behaviors of university students who major in music, dance and theater. And then, the study proposed the 36 facets with the 9 main facet categories suitable for performing arts and also proposed 27 descriptive elements suitable for performing arts contents. Finally, the study developed the performing arts contents retrieval system based faceted navigation interface with 3,360 experimental data and conducted an in-depth interview in terms of usability, serendipity, and efficiency. The applying the faceted navigations for searching performing arts contents will help users access and utilize them in the retrieval system and moreover satisfy user demands.