• Title/Summary/Keyword: Automatic Retrieval

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A Study of Designing the Han-Guel Thesaurus Browser for Automatic Information Retrieval (자동정보검색을 위한 한글 시소러스 브라우저 구축에 관한 연구)

  • Seo, Whee
    • Journal of Korean Library and Information Science Society
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    • v.31 no.2
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    • pp.279-302
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    • 2000
  • This study is to develop a new automatic system for the Korean thesaurus browser by which we can automatically control all the processes of searching queries such as, representation, generation, extension and construction of searching strategy and feedback searching. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of database system, automatic indexing, clustering technique, establishing and expressing thesaurus, and automatic information retrieval technique. The results proved by this system are as follows: 1)By using the new automatic thesaurus browser developed by the new algorithm, we can perform information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, information retrieval technique, and retrieval feedback. Thus it turns out that even the beginner user can easily access special terms about the field of a specific subject. 2) The thesaurus browser in this paper has such merits as the easiness of establishing, the convenience of using, and the good results of information retrieval in terms of the rate of speed, degree, and regeneration. Thus, it t m out very pragmatic.

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A Theoretical Study of Designing Thesaurus Browser by Clustering Algorithm (클러스터링을 이용한 시소러스 브라우저의 설계에 대한 이론적 연구)

  • Seo, Hwi
    • Journal of Korean Library and Information Science Society
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    • v.30 no.3
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    • pp.427-456
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    • 1999
  • This paper deals with the problems of information retrieval through full-test database which arise from both the deficiency of searching strategies or methods by information searcher and the difficulties of query representation, generation, extension, etc. In oder to solve these problems, we should use automatic retrieval instead of manual retrieval in the past. One of the ways to make the gap narrow between the terms by the writers and query by the searchers is that the query should be searched with the terms which the writers use. Thus, the preconditions which should be taken one accorded way to solve the problems are that all areas of information retrieval such as should taken one accorded way to solve the problems are that all areas of information retrieval such as contents analysis, information structure, query formation, query evaluation, etc. should be solved as a coherence way. We need to deal all the ares of automatic information retrieval for the efficiency of retrieval thought this paper is trying to solve the design of thesaurus browser. Thus, this paper shows the theoretical analyses about the form of information retrieval, automatic indexing, clustering technique, establishing and expressing thesaurus, and information retrieval technique. As the result of analyzing them, this paper shows us theoretical model, that is to say, the thesaurus browser by clustering algorithm. The result in the paper will be a theoretical basis on new retrieval algorithm.

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An Experiment on Automatic Query Modification In Information Retrieval Using the Relevance Feedback (이용자 피이드백에 의한 검색질문의 자동 수정에 관한 연구)

  • Shin, Young-Shil
    • Journal of the Korean Society for information Management
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    • v.2 no.1
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    • pp.108-135
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    • 1985
  • When an information retrieval system is implemented on-line, users can interact with the system to improve the searches. There are studies which achieved dramatic improvements in system effectiveness by using automatic relevance feedback, a technique for reformulating a patron query based on initial retrieval result. In this thesis, an automatic query modification model was applied to a controlled keyword system.

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A Study on Automatic Keyword Classification (용어의 자동분류에 관한 연구)

  • Seo, Eun-Gyoung
    • Journal of the Korean Society for information Management
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    • v.1 no.1
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    • pp.78-99
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    • 1984
  • In this paper, the automatic keyword classification which is one of the automatic construction methods of retrieval thesaurus is experimented to the Korean language on the basis that the use of retrieval thesaurus would increase the efficiency of information retrieval in the natural language retrieval system searching machine-readable data base. Furthermore, this paper proposes the application methods. In this experiment, the automatic keyword classification was based on the assumption that semantic relationships between terms can be found out by the statistical patterns of terms occurring in a text.

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A Study of Designing the Automatic Information Retrieval System based on Natural Language (자연어를 이용한 자동정보검색시스템 구축에 관한 연구)

  • Seo, Hwi
    • Journal of the Korean Society for Library and Information Science
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    • v.35 no.4
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    • pp.141-160
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    • 2001
  • This study is to develop a new system for conducting the information retrieval automatically. The system in this study is programmed by Delphi 4.0(PASCAL) and consists of automatic indexing, clustering technique, establishing and expressing term hierarchic relation, and automatic information retrieval technique. Thus this browser system can automatically control all the processes of information searching such as representation, generation and extension of queries and construction of searching strategy and feedback searching.

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An Automatic and Scalable Application Crawler for Large-Scale Mobile Internet Content Retrieval

  • Huang, Mingyi;Lyu, Yongqiang;Yin, Hao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.10
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    • pp.4856-4872
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    • 2018
  • The mobile internet has grown ubiquitous across the globe with the widespread use of smart devices. However, the designs of modern mobile operating systems and their applications limit content retrieval with mobile applications. The mobile internet is not as accessible as the traditional web, having more man-made restrictions and lacking a unified approach for crawling and content retrieval. In this study, we propose an automatic and scalable mobile application content crawler, which can recognize the interaction paths of mobile applications, representing them as interaction graphs and automatically collecting content according to the graphs in a parallel manner. The crawler was verified by retrieving content from 50 non-game applications from the Google Play Store using the Android platform. The experiment showed the efficiency and scalability potential of our crawler for large-scale mobile internet content retrieval.

Intermediary Systems for Bibliographic Information Retrieval

  • Yoo, Ja Kyung
    • Journal of the Korean Society for information Management
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    • v.2 no.2
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    • pp.38-70
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    • 1985
  • The purpose of this paper is to provide a review of the literature on the role of end-user intermediary systems in information retrieval. The paper starts with an introduction pointing out the problems involved in conventional retrieval system. The next section covers the major developments in the field of intermediary systems including natural language processing, automatic query formulation, relevance feedback, and automatic query refinement. The paper concludes with a general overview of the current state of the art and its future implications in information retrieval.

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A Semantic-based Video Retrieval System Using the Automatic Indexing Agent (자동 인덱싱 에이전트를 이용한 의미기반 비디오 검색 시스템)

  • Kim Sam-Keun;Lee Jong-Hee;Yoon Sun-Hee;Lee Keun-Soo;Seo Jeong-Min
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.127-137
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    • 2006
  • In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the automatic indexing agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

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Resolving the Ambigities in World Sense by using Automatic Keyword Network in Information Retrieval (정보검색에서의 어의 중의성 해소를 위한 자동 키워드망의 이용)

  • Kim, Jung-Sae;Jang, Duk-Sung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.12
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    • pp.3855-3865
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    • 2000
  • The automatic indexing is a compulsory part for the text retrieval system. However it is impossible to rank the appropriate texts at top. Furthermore, it is more difficult to prevent to rank the inappropriate texts having homonyms at top by only the automatic indexing. In this paper, we proposed the two-level retrieval system to enhance the retrieval efficiency, in which Automatic Keyword Network (AKN) is used at the second-level process. The firsHevel search is carried out with an inverted index file generated by the automatic indexing. On the other hand the second-level search exploits AKN based on the degree of asslxiation between terms. We have developed several formulas for rearranging the rank of texts at second-level search, and evaluated the performance of the effects of them on resolving the word sense ambiguities.

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Similar Image Retrieval Technique based on Semantics through Automatic Labeling Extraction of Personalized Images

  • Jung-Hee, Seo
    • Journal of information and communication convergence engineering
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    • v.22 no.1
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    • pp.56-63
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    • 2024
  • Despite the rapid strides in content-based image retrieval, a notable disparity persists between the visual features of images and the semantic features discerned by humans. Hence, image retrieval based on the association of semantic similarities recognized by humans with visual similarities is a difficult task for most image-retrieval systems. Our study endeavors to bridge this gap by refining image semantics, aligning them more closely with human perception. Deep learning techniques are used to semantically classify images and retrieve those that are semantically similar to personalized images. Moreover, we introduce a keyword-based image retrieval, enabling automatic labeling of images in mobile environments. The proposed approach can improve the performance of a mobile device with limited resources and bandwidth by performing retrieval based on the visual features and keywords of the image on the mobile device.