• Title/Summary/Keyword: human-computer information retrieval

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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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    • 1998.06a
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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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User Adaptation Using User Model in Intelligent Image Retrieval System (지능형 화상 검색 시스템에서의 사용자 모델을 이용한 사용자 적응)

  • Kim, Yong-Hwan;Rhee, Phill-Kyu
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.12
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    • pp.3559-3568
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    • 1999
  • The information overload with many information resources is an inevitable problem in modern electronic life. It is more difficult to search some information with user's information needs from an uncontrolled flood of many digital information resources, such as the internet which has been rapidly increased. So, many information retrieval systems have been researched and appeared. In text retrieval systems, they have met with user's information needs. While, in image retrieval systems, they have not properly dealt with user's information needs. In this paper, for resolving this problem, we proposed the intelligent user interface for image retrieval. It is based on HCOS(Human-Computer Symmetry) model which is a layed interaction model between a human and computer. Its' methodology is employed to reduce user's information overhead and semantic gap between user and systems. It is implemented with machine learning algorithms, decision tree and backpropagation neural network, for user adaptation capabilities of intelligent image retrieval system(IIRS).

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The Study of Automatic Hypertext Generation using the Syntactic and Semantic Similarity (구문적 유사도와 의미적 유사도를 이용한 하이퍼텍스트 자동생성에 관한 연구)

  • Kim, Mun-Seok;Nam, Se-Jin;Shin, Dong-Wook
    • Annual Conference on Human and Language Technology
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    • 1996.10a
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    • pp.424-429
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    • 1996
  • 본 논문에는 일반문서를 대상으로 하여 그 문사를 하이퍼텍스트(hypertext)로 자동변환하는 기법을 제안하고자 한다. 자동변환의 과정은 대상 문서에서 키워드(keyword)의 인식, 문서를 노드(node) 단위로 분리, 키워드로부터 노드로의 링크(ink) 생성의 3 단계로 이루어 진다. 기존의 연구에서는 문서에서 노드를 분리하는데 구문적 유사도만을 이용하는데, 본 논문에서는 양질의 하이퍼텍스트를 생성하기 위하여 구문적 유사도(syntactic similarity)뿐만 아니라 의미적 유사도(semantic similarity)를 사용한다. 구문적 유사도는 tf*idf와 벡터 곱(vector product)을 이용하고, 의미적 유사도는 시소러스(thesaurus)와 부분부합(partial match)을 이용하여 계산되어 진다. 또 링크 생성시 잘못된 링크의 생성을 막기 위하여 시소러스를 이용하여 시소러스에 존재하는 용어에 한해서 링크를 생성한다.

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Document filtering for automatic construct ion of Answer Set (Answer set 자동 구축을 위한 문서 필터링)

  • Jeong, Yong-Kyo;Shin, Seug-Eun;Oh, Hyo-Jung;Jang, Myung-Gil;Seo, Young-Hoon
    • Annual Conference on Human and Language Technology
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    • 2002.10e
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    • pp.253-258
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    • 2002
  • 본 논문은 의미기반 정보검색 소프트웨어 기술에서 정답 문서 자동 구축을 위한 문서 필터링기법을 제안한다. 문서 필터링은 1차 질의어와 문서간의 유사도와 2차 질의어와 문서간의 유사도를 이용하여 이루어지며, 1차 질의어와 문서간의 유사도를 구하기 위하여 개념 망과 백과사전 정보를 이용한 1차 질의어 확장 과정을 수행하고, 화장된 질의어와 문서와의 유사도를 계산한다. 1차 확장 질의어를 이용해 얻어진 결과 중 유사도가 상위 10%에 속하는 문서를 이용하여 2차 질의어 확장을 한다. 2차 질의어 확장은 상위 10% 문서에 출현하는 명사중 문서 출현 빈도가 임계치 이상인 명사를 선택하여 이루어지고, 그것을 이용하여 문서의 유사도를 계산한다. 이렇게 얻어진 두 가지의 유사도를 결합하여 문서들을 순위화하고 Accept Point를 이용하여 문서를 필터링한다.

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A novel page replacement policy associated with ACT-R inspired by human memory retrieval process (인간 기억 인출 과정을 응용하여 설계된 ACT-R 기반 페이지 교체 정책)

  • Roh, Hong-Chan;Park, Sang-Hyun
    • The KIPS Transactions:PartD
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    • v.18D no.1
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    • pp.1-8
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    • 2011
  • The cache structure, which is designed for assuring fast accesses to frequently accessed data, resides on the various levels of computer system hierarchies. Many studies on this cache structure have been conducted and thus many page-replacement algorithms have been proposed. Most of page-replacement algorithms are designed on the basis of heuristic methods by using their own criteria such as how recently pages are accessed and how often they are accessed. This data-retrieval process in computer systems is analogous to human memory retrieval process since the retrieval process of human memory depends on frequency and recency of the retrieval events as well. A recent study regarding human memory cognition revealed that the possibility of the retrieval success and the retrieval latency have a strong correlation with the frequency and recency of the previous retrieval events. In this paper, we propose a novel page-replacement algorithm by utilizing the knowledge from the recent research regarding human memory cognition. Through a set of experiments, we demonstrated that our new method presents better hit-ratio than the LRFU algorithm which has been known as the best performing page-replacement algorithm for DBMS caches.

Detection of face region for an effective News Retrieval (효과적인 뉴스 검색을 위한 얼굴 영역의 추출)

  • 윤일태;정승도;조정원;배영래;최병욱
    • Proceedings of the IEEK Conference
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    • 2001.06c
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    • pp.81-84
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    • 2001
  • The retrieval techniques of multimedia contents have been developed along with MPEG-7. But as human being distinguishes objects with the eyesight, researches for high retrieval efficiency applied a high level computer vision technology are difficult because of the increase of processing time caused by complexity of algorithm, and the difficulty of an implementation. In this paper, for an effective news retrieval using the human face information, we suggest a method which extracts face information like as location, size and number of the face in the news video, and then we prove the validity of method by experiment.

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Content-based Image Retrieval Using Data Fusion Strategy (데이터 융합을 이용한 내용기반 이미지 검색에 관한 연구)

  • Paik, Woo-Jin;Jung, Sun-Eun;Kim, Gi-Young;Ahn, Eui-Gun;Shin, Moon-Sun
    • Journal of the Korean Society for information Management
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    • v.25 no.2
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    • pp.49-68
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    • 2008
  • In many information retrieval experiments, the data fusion techniques have been used to achieve higher effectiveness in comparison to the single evidence-based retrieval. However, there had not been many image retrieval studies using the data fusion techniques especially in combining retrieval results based on multiple retrieval methods. In this paper, we describe how the image retrieval effectiveness can be improved by combining two sets of the retrieval results using the Sobel operator-based edge detection and the Self Organizing Map(SOM) algorithms. We used the clip art images from a commercial collection to develop a test data set. The main advantage of using this type of the data set was the clear cut relevance judgment, which did not require any human intervention.

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.

Interactive Information Retrieval: An Introduction

  • Borlund, Pia
    • Journal of Information Science Theory and Practice
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    • v.1 no.3
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    • pp.12-32
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    • 2013
  • The paper introduces the research area of interactive information retrieval (IIR) from a historical point of view. Further, the focus here is on evaluation, because much research in IR deals with IR evaluation methodology due to the core research interest in IR performance, system interaction and satisfaction with retrieved information. In order to position IIR evaluation, the Cranfield model and the series of tests that led to the Cranfield model are outlined. Three iconic user-oriented studies and projects that all have contributed to how IIR is perceived and understood today are presented: The MEDLARS test, the Book House fiction retrieval system, and the OKAPI project. On this basis the call for alternative IIR evaluation approaches motivated by the three revolutions (the cognitive, the relevance, and the interactive revolutions) put forward by Robertson & Hancock-Beaulieu (1992) is presented. As a response to this call the 'IIR evaluation model' by Borlund (e.g., 2003a) is introduced. The objective of the IIR evaluation model is to facilitate IIR evaluation as close as possible to actual information searching and IR processes, though still in a relatively controlled evaluation environment, in which the test instrument of a simulated work task situation plays a central part.