• Title, Summary, Keyword: Intelligent Information Retrieval Algorithm

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Interactive Genetic Algorithm for Content-based Image Retrieval

  • Lee, Joo-Young;Cho, Sung-Bae
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.479-484
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    • 1998
  • As technology in a computer hardware and software advances, efficient information retrieval from multimedia database gets highly demanded. Recently, it has been actively exploited to retrieve information based on the stored contents. However, most of the methods emphasize on the points which are far from human intuition or emotion. In order to overcome this shortcoming , this paper attempts to apply interactive genetic algorithm to content-based image retrieval. A preliminary result with subjective test shows the usefulness of this approach.

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A Study of Designing the Intelligent Information Retrieval System by Automatic Classification Algorithm (자동분류 알고리즘을 이용한 지능형 정보검색시스템 구축에 관한 연구)

  • Seo, Whee
    • Journal of Korean Library and Information Science Society
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    • v.39 no.4
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    • pp.283-304
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    • 2008
  • This is to develop Intelligent Retrieval System which can automatically present early query's category terms(association terms connected with knowledge structure of relevant terminology) through learning function and it changes searching form automatically and runs it with association terms. For the reason, this theoretical study of Intelligent Automatic Indexing System abstracts expert's index term through learning and clustering algorism about automatic classification, text mining(categorization), and document category representation. It also demonstrates a good capacity in the aspects of expense, time, recall ratio, and precision ratio.

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Image Retrieval Method Based on IPDSH and SRIP

  • Zhang, Xu;Guo, Baolong;Yan, Yunyi;Sun, Wei;Yi, Meng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.5
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    • pp.1676-1689
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    • 2014
  • At present, the Content-Based Image Retrieval (CBIR) system has become a hot research topic in the computer vision field. In the CBIR system, the accurate extractions of low-level features can reduce the gaps between high-level semantics and improve retrieval precision. This paper puts forward a new retrieval method aiming at the problems of high computational complexities and low precision of global feature extraction algorithms. The establishment of the new retrieval method is on the basis of the SIFT and Harris (APISH) algorithm, and the salient region of interest points (SRIP) algorithm to satisfy users' interests in the specific targets of images. In the first place, by using the IPDSH and SRIP algorithms, we tested stable interest points and found salient regions. The interest points in the salient region were named as salient interest points. Secondary, we extracted the pseudo-Zernike moments of the salient interest points' neighborhood as the feature vectors. Finally, we calculated the similarities between query and database images. Finally, We conducted this experiment based on the Caltech-101 database. By studying the experiment, the results have shown that this new retrieval method can decrease the interference of unstable interest points in the regions of non-interests and improve the ratios of accuracy and recall.

Cross-Lingual Text Retrieval Based on a Knowledge Base (지식베이스에 기반한 다언어 문서 검색)

  • Choi, Myeong-Bok;Jo, Jun
    • The Journal of The Institute of Internet, Broadcasting and Communication
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    • v.10 no.1
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    • pp.21-32
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    • 2010
  • User query formation highly acts on the effectiveness of information retrieval when we retrieve documents from the general domain as a web. This thesis proposes a intelligent information retrieval method based on a cross-lingual knowledge base to effectively perform a cross-lingual text retrieval from the web. The inferred knowledge from the cross-lingual knowledge base helps user's word association to make up user query easily and exactly for effective cross-lingual text information retrieval. This thesis develops user's query reformation algorithm and experiments it with Korean and English web. Experimental results show that the algorithm based on the proposed knowledge base is much more effective than without knowledge base in the cross-lingual text retrieval.

A New Approach of Domain Dictionary Generation

  • Xi, Su Mei;Cho, Young-Im;Gao, Qian
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.1
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    • pp.15-19
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    • 2012
  • A Domain Dictionary generation algorithm based on pseudo feedback model is presented in this paper. This algorithm can increase the precision of domain dictionary generation algorithm. The generation of Domain Dictionary is regarded as a domain term retrieval process: Assume that top N strings in the original retrieval result set are relevant to C, append these strings into the dictionary, retrieval again. Iterate the process until a predefined number of domain terms have been generated. Experiments upon corpus show that the precision of pseudo feedback model based algorithm is much higher than existing algorithms.

A Proposal of Multimedia Intelligent Database for Medical Diagnosis

  • MODEGI, Toshio;IISAKU, Shun-ichi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.61-66
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    • 1997
  • For constructing an intelligent multimedia database system for medical diagnosis, we are focusing on two technological points. One is a retrieval algorithm of databases, and the other is a coding algorithm of multimedia contents. For the first, previously we proposed a front-end database preprocessor called“keyword-network”, and in this paper we present its extended model providing an intelligent logical AND searching function especially for medical differential diagnosis. For the second, we present examples of multimedia intellectual coding methods for cardiovascular examination records.

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Query Space Exploration Using Genetic Algorithm

  • Lee, Jae-Hoon;Kim, Young-Cheon;Lee, Sung-Joo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.683-689
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    • 2003
  • Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

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Query Space Exploration Model Using Genetic Algorithm

  • Lee, Jae-Hoon;Lee, Sung-Joo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.2
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    • pp.222-226
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    • 2003
  • Information retrieval must be able to search the most suitable document that user need from document set. If foretell document adaptedness by similarity degree about QL(Query Language) of document, documents that search person does not require are searched. In this paper, showed that can search the most suitable document on user's request searching document of the whole space using genetic algorithm and used knowledge-base operator to solve various model's problem.

Image Feature Representation Using Code Vectors for Retrieval

  • Nishat, Ahmad;Zhao, Hui;Park, Jong-An;Park, Seung-Jin;Yang, Won-II
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.8 no.3
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    • pp.122-130
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    • 2009
  • The paper presents an algorithm which uses code vectors to represent comer geometry information for searching the similar images from a database. The comers have been extracted by finding the intersections of the detected lines found using Hough transform. Taking the comer as the center coordinate, the angles of the intersecting lines are determined and are represented using code vectors. A code book has been used to code each comer geometry information and indexes to the code book are generated. For similarity measurement, the histogram of the code book indexes is used. This result in a significant small size feature matrix compared to the algorithms using color features. Experimental results show that use of code vectors is computationally efficient in similarity measurement and the comers being noise invariant produce good results in noisy environments.

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