• Title/Summary/Keyword: information retrieval.

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Hybrid Video Information System Supporting Content-based Retrieval and Similarity Retrieval (비디오의 의미검색과 유사성검색을 위한 통합비디오정보시스템)

  • Yun, Mi-Hui;Yun, Yong-Ik;Kim, Gyo-Jeong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.8
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    • pp.2031-2041
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    • 1999
  • In this paper, we present the HVIS (Hybrid Video Information System) which bolsters up meaning retrieval of all the various users by integrating feature-based retrieval and annotation-based retrieval of unformatted formed and massive video data. HVIS divides a set of video into video document, sequence, scene and object to model the metadata and suggests the Two layered Hybrid Object-oriented Metadata Model(THOMM) which is composed of raw-data layer for physical video stream, metadata layer to support annotation-based retrieval, content-based retrieval, and similarity retrieval. Grounded on this model, we presents the video query language which make the annotation-based query, content-based query and similar query possible and Video Query Processor to process the query and query processing algorithm. Specially, We present the similarity expression to appear degree of similarity which considers interesting of user. The proposed system is implemented with Visual C++, ActiveX and ORACLE.

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Contents-based Image Retrieval Using Color & Edge Information (칼라와 에지 정보를 이용한 내용기반 영상 검색)

  • Park, Dong-Won;An, Syungog;Ma, Ming;Singh, Kulwinder
    • The Journal of Korean Association of Computer Education
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    • v.8 no.1
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    • pp.81-91
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    • 2005
  • In this paper we present a novel approach for image retrieval using color and edge information. We take into account the HSI(Hue, Saturation and Intensity) color space instead of RGB space, which emphasizes more on visual perception. In our system colors in an image are clustered into a small number of representative colors. The color feature descriptor consists of the representative colors and their percentages in the image. An improved cumulative color histogram distance measure is defined for this descriptor. And also, we have developed an efficient edge detection technique as an optional feature to our retrieval system in order to surmount the weakness of color feature. During the query processing, both the features (color, edge information) could be integrated for image retrieval as well as a standalone entity, by specifying it in a certain proportion. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

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An Encrypted Speech Retrieval Scheme Based on Long Short-Term Memory Neural Network and Deep Hashing

  • Zhang, Qiu-yu;Li, Yu-zhou;Hu, Ying-jie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.6
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    • pp.2612-2633
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    • 2020
  • Due to the explosive growth of multimedia speech data, how to protect the privacy of speech data and how to efficiently retrieve speech data have become a hot spot for researchers in recent years. In this paper, we proposed an encrypted speech retrieval scheme based on long short-term memory (LSTM) neural network and deep hashing. This scheme not only achieves efficient retrieval of massive speech in cloud environment, but also effectively avoids the risk of sensitive information leakage. Firstly, a novel speech encryption algorithm based on 4D quadratic autonomous hyperchaotic system is proposed to realize the privacy and security of speech data in the cloud. Secondly, the integrated LSTM network model and deep hashing algorithm are used to extract high-level features of speech data. It is used to solve the high dimensional and temporality problems of speech data, and increase the retrieval efficiency and retrieval accuracy of the proposed scheme. Finally, the normalized Hamming distance algorithm is used to achieve matching. Compared with the existing algorithms, the proposed scheme has good discrimination and robustness and it has high recall, precision and retrieval efficiency under various content preserving operations. Meanwhile, the proposed speech encryption algorithm has high key space and can effectively resist exhaustive attacks.

BADA-$IV/I^2R$: Design & Implementation of an Efficient Content-based Image Retrieval System using a High-Dimensional Image Index Structure (바다-$IV/I^2R$: 고차원 이미지 색인 구조를 이용한 효율적인 내용 기반 이미지 검색 시스템의 설계와 구현)

  • Kim, Yeong-Gyun;Lee, Jang-Seon;Lee, Hun-Sun;Kim, Wan-Seok;Kim, Myeong-Jun
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.2S
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    • pp.678-691
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    • 2000
  • A variety of multimedia applications require multimedia database management systems to manage multimedia data, such as text, image, and video, as well as t support content-based image or video retrieval. In this paper we design and implement a content-based image retrieval system, BADA-IV/I$^2$R(Image Information Retrieval), which is developed based on BADA-IV multimedia database management system. In this system image databases can be efficiently constructed and retrieved with the visual features, such as color, shape, and texture, of image. we extend SQL statements to define image query based on both annotations and visual features of image together. A high-dimensional index structure, called CIR-tree, is also employed in the system to provide an efficient access method to image databases. We show that BADA-IV/I$^2$R provides a flexible way to define query for image retrieval and retrieves image data fast and effectively: the effectiveness and performance of image retrieval are shown by BEP(Bull's Eye Performance) that is used to measure the retrieval effectiveness in MPEG-7 and comparing the performance of CIR-tree with those of X-tree and TV-tree, respectively.

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Audio Fingerprint Retrieval Method Based on Feature Dimension Reduction and Feature Combination

  • Zhang, Qiu-yu;Xu, Fu-jiu;Bai, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.2
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    • pp.522-539
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    • 2021
  • In order to solve the problems of the existing audio fingerprint method when extracting audio fingerprints from long speech segments, such as too large fingerprint dimension, poor robustness, and low retrieval accuracy and efficiency, a robust audio fingerprint retrieval method based on feature dimension reduction and feature combination is proposed. Firstly, the Mel-frequency cepstral coefficient (MFCC) and linear prediction cepstrum coefficient (LPCC) of the original speech are extracted respectively, and the MFCC feature matrix and LPCC feature matrix are combined. Secondly, the feature dimension reduction method based on information entropy is used for column dimension reduction, and the feature matrix after dimension reduction is used for row dimension reduction based on energy feature dimension reduction method. Finally, the audio fingerprint is constructed by using the feature combination matrix after dimension reduction. When speech's user retrieval, the normalized Hamming distance algorithm is used for matching retrieval. Experiment results show that the proposed method has smaller audio fingerprint dimension and better robustness for long speech segments, and has higher retrieval efficiency while maintaining a higher recall rate and precision rate.

A screening study of human factors variables in designing multimedia information retrieval systems (정보습득용 멀티미디어 시스템의 인간공학적 설계변수 선별)

  • 김미정;한성호
    • Proceedings of the ESK Conference
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    • 1995.10a
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    • pp.56-61
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    • 1995
  • Multimedia systems present information by using various media, for example, video, sound, music, animation, movie, etc., in addition to the text which has long been used for conveying the information. Among many multimedia applications, the multimedia information retrieval systems commercialized in the form of multimedia encyclopedia CD-ROMs, benefit by using various media for their ability to present information in an efficient and complete way. But using various media may cause end users' confusion and furthermore, poor user-interface design often exacerbates the systems. For appropriate design of the user interface of multimedia information retrieval systems, we investigated the characteristics of the multimedia information retrieval systems and listed 35 variables that might affect the usability of the user interface. And we selected 10 variables through some procedures such as brainstorming, literature survey, expert opinion, relevance analysis and feasibility analysis, in order to perform a screening study which will remarkably reduce the cost and time in conducting subsequent human factors experiments.

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Modified Element Type ID Representation for XML Structure Retrieval

  • Jin, Seung-Hoon;Kim, Soon-Cheol;Kim, Jong-Wan;Kang, Sin-Jae
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.3
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    • pp.61-68
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    • 2003
  • In this paper, a representation method for structure information retrieval without schema and DTD of XML documents is presented. While existing researches have used DTD or schema to extract structure information, we extract structure information directly from XML documents. Especially the well-formed XML documents are only required to retrieve documents in the proposed method. Thus it can retrieve more general and various documents easily compared to the existing XML retrieval systems requiring DTD or schema. Experimental result indicates that the proposed method retrieves effectively structure information of XML documents independently to DTD information.

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Content Based Image Retrieval Using Combined Features of Shape, Color and Relevance Feedback

  • Mussarat, Yasmin;Muhammad, Sharif;Sajjad, Mohsin;Isma, Irum
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.12
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    • pp.3149-3165
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    • 2013
  • Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

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 EFFICIENT DENSITY BASED ANT COLONY APPROACH ON WEB DOCUMENT CLUSTERING

  • M. REKA
    • Journal of applied mathematics & informatics
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    • v.41 no.6
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    • pp.1327-1339
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    • 2023
  • World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.