• Title/Summary/Keyword: bookmark

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Personalized Bookmark System for the Web Environment (웹 환경에서의 개인화 북마크 시스템)

  • Jin Yong-Seok;Lee Sang-Joon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2006.05a
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    • pp.804-806
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    • 2006
  • There have been presented many solutions to improve Web accessibilities. A bookmark system is one of those convenient solutions. The convenience and usefulness of bookmark system is decreased when the registered contents arc increased. In this study, we proposed the personalized bookmark system. With this system, the bookmark contents are automatically updated by reflecting personal user's web preferences. And by managing the bookmark system with the server system, users can access the bookmark system at any place.

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Comparison of results between modified-Angoff and bookmark methods for estimating cut score of the Korean medical licensing examination

  • Yim, Mikyoung
    • Korean journal of medical education
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    • v.30 no.4
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    • pp.347-357
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    • 2018
  • Purpose: The purpose of this study was to apply alternative standard setting methods for the Korean Medical Licensing Examination (KMLE), a criterion-referenced written examination, and to compare them to the conventional cut score used on the KMLE. Methods: The process and results of criterion-referenced standard settings (i.e., the modified-Angoff and bookmark methods) were evaluated. The ratio of passing and failing examinees determined using these alternative standard setting methods was compared to the results of the conventional criteria. Additionally, the external, internal and procedural evaluation of these methods were reviewed. Results: The modified-Angoff method yielded the highest cut score, followed sequentially by the conventional method and the bookmark method. The classification agreement between the modified-Angoff and bookmark methods was 0.720 measured by Cohen's ${\kappa}$ coefficient. The intra-panelist classification consistency of modified-Angoff method was higher than bookmark method. However, the inter-panelist classification consistency was vice versa. The standard setting panelists' survey results showed that the procedures of both methods were satisfactory, but panelists had more confidence in the results of the modified-Angoff method. Conclusion: The modified-Angoff method showed results that were more similar to those of the conventional method. Both new methods showed very high concordance with the conventional method, as well as with each other. The modified-Angoff method was considered feasible for adoption on the KMLE. The standard setting panelists responded positively to the modified-Angoff method in terms of its practical applicability, despite certain advantages of the bookmark method.

Using Behavior Analysis and Improvement of Bookmark as Web nformation Management Tool (웹 정보 수집 관리 도구로서의 북마크 이용행태 분석을 통한 개선방안 연구)

  • Min, Ji-Yeon;Lee, Jee-Yeon
    • Journal of the Korean Society for information Management
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    • v.26 no.4
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    • pp.59-80
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    • 2009
  • As the amount of web information grows, a bookmark has become an important tool to reuse web information effectively which is relevant to users' information needs. Thus, this study aimed to investigate how bookmarks are used as a management tool of web information, and what functions users require concerned with it. For this purpose, semi-structured interviews and observations were carried out from 5 respondents, and a survey was conducted to investigate the relationship between bookmark using behaviors and requirements for function improvement. The users who use bookmark less frequently think bookmark feature essential for the purpose of reusing web information.

Design and Implementation of Educational Information Sharing Systems using Bookmark (즐겨찾기를 이용한 교육용 정보공유시스템의 설계 및 구현)

  • Han, Sun-Gwan
    • The Journal of Korean Association of Computer Education
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    • v.7 no.6
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    • pp.77-84
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    • 2004
  • This study proposed the agent system for educational information sharing using bookmark. In order to search and share the educational information effectively, we designed DAML+OIL-typed bookmark information. Proposed system in this study had the P2P type based on Client-Server type. We implemented the bookmark agent that has the intelligent characteristics, that is, automatic categorization of peers and documents, autonomous communication between agents using DAML, and delicate information searching using the ontology dictionary in Semantic Web environment. Hereafter, this study will contribute to activate sharing and searching educational information as well as proposed system will offer the important technologies for SCORM-based e-learning environment.

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Personalized Bookmark Search Word Recommendation System based on Tag Keyword using Collaborative Filtering (협업 필터링을 활용한 태그 키워드 기반 개인화 북마크 검색 추천 시스템)

  • Byun, Yeongho;Hong, Kwangjin;Jung, Keechul
    • Journal of Korea Multimedia Society
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    • v.19 no.11
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    • pp.1878-1890
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    • 2016
  • Web 2.0 has features produced the content through the user of the participation and share. The content production activities have became active since social network service appear. The social bookmark, one of social network service, is service that lets users to store useful content and share bookmarked contents between personal users. Unlike Internet search engines such as Google and Naver, the content stored on social bookmark is searched based on tag keyword information and unnecessary information can be excluded. Social bookmark can make users access to selected content. However, quick access to content that users want is difficult job because of the user of the participation and share. Our paper suggests a method recommending search word to be able to access quickly to content. A method is suggested by using Collaborative Filtering and Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare by 'Delicious' and "Feeltering' with our system.

Automated Video Clip Creation Using Time-based Social Bookmark Clustering (소셜 북마크의 시간 정보 클러스터링을 이용한 비디오 클립 생성 자동화)

  • Han, Sung-Hee;Lee, Jae-Ho;Kang, Dae-Kap
    • Journal of Broadcast Engineering
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    • v.15 no.1
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    • pp.144-147
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    • 2010
  • Recently the change of content consumption trend activated the social video sharing platform and the video clip itself. There have been intensive interests and efforts to automatically abstract compact and meaningful video clips. In this paper, we propose a method which use the clustering of the bookmark data created by collective intelligence instead of using the video content analysis. The partitional clustering of points in 2-dimensional space derived from the bookmark data make it possible to abstract highlights effectively. The method is enhanced by the 1-dimensional accumulated bookmark count graph. Experiments on the real data from KBS internet service show the effectiveness of the proposed method.

Bookmark for Multimedia Content Having Multiple Variations (변형을 갖는 멀티미디어 콘텐트에 대한 북마크)

  • Yeom, Ji-Hyeon;Kim, Myoung-Hoon;Sull, Sang-Hoon;Kim, Hyeok-Man
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.7
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    • pp.489-494
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    • 2009
  • Since multimedia content is often independently encoded into multiple variations having diverse bandwidths, resolutions and compression formats, the same segment might be stored at different temporal positions within the variations. In this paper, we present a durable multimedia bookmark mechanism which provides a convenient way of switching to any variation before or during playback of the multimedia content, without experiencing temporal discontinuity or overlapping a portion of the content. We also present a new multimedia bookmark player with which users can manage a personal collection of bookmarks with an intuitive visual interface.

Personalized Bookmark Recommendation System Using Tag Network (태그 네트워크를 이용한 개인화 북마크 추천시스템)

  • Eom, Tae-Young;Kim, Woo-Ju;Park, Sang-Un
    • The Journal of Society for e-Business Studies
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    • v.15 no.4
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    • pp.181-195
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    • 2010
  • The participation and share between personal users are the driving force of Web 2.0, and easily found in blog, social network, collective intelligence, social bookmarking and tagging. Among those applications, the social bookmarking lets Internet users to store bookmarks online and share them, and provides various services based on shared bookmarks which people think important.Delicious.com is the representative site of social bookmarking services, and provides a bookmark search service by using tags which users attach to the bookmarks. Our paper suggests a method re-ranking the ranks from Delicious.com based on user tags in order to provide personalized bookmark recommendations. Moreover, a method to consider bookmarks which have tags not directly related to the user query keywords is suggested by using tag network based on Jaccard similarity coefficient. The performance of suggested system is verified with experiments that compare the ranks by Delicious.com with new ranks of our system.

A Web Contents Ranking System using Related Tag & Similar User Weight (연관 태그 및 유사 사용자 가중치를 이용한 웹 콘텐츠 랭킹 시스템)

  • Park, Su-Jin;Lee, Si-Hwa;Hwang, Dae-Hoon
    • Journal of Korea Multimedia Society
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    • v.14 no.4
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    • pp.567-576
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    • 2011
  • In current Web 2.0 environment, one of the most core technology is social bookmarking which users put tags and bookmarks to their interesting Web pages. The main purpose of social bookmarking is an effective information service by use of retrieval, grouping and share based on user's bookmark information and tagging result of their interesting Web pages. But, current social bookmarking system uses the number of bookmarks and tag information separately in information retrieval, where the number of bookmarks stand for user's degree of interest on Web contents, information retrieval, and classification serve the purpose of tag information. Because of above reason, social bookmarking system does not utilize effectively the bookmark information and tagging result. This paper proposes a Web contents ranking algorithm combining bookmarks and tag information, based on preceding research on associative tag extraction by tag clustering. Moreover, we conduct a performance evaluation comparing with existing retrieval methodology for efficiency analysis of our proposed algorithm. As the result, social bookmarking system utilizing bookmark with tag, key point of our research, deduces a effective retrieval results compare with existing systems.

Bookmark Classification Agent Based on Naive Bayesian Learning Method (나이브 베이지안 학습법에 기초한 북마크 분류 에이전트)

  • 최정민;김인철
    • Proceedings of the Korea Multimedia Society Conference
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    • 2000.04a
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    • pp.405-408
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    • 2000
  • 최근 인터넷의 발전으로 많은 정보와 지식을 우리는 인터넷에서 제공받을 수 있게되었다. 인터넷에 존재하는 정보는 수많은 웹서버에 산재되어 있으며, 정보의 위치는 주소(URL)를 가지고 존재하게 되는데 사용자는 자신이 관심있는 정보의 주소를 저장하기 위하여 웹브라우저 북마크(Bookmark)기능을 사용한다. 그러나 북마크 기능은 웹문서의 주소 저장에 일차적인 목적을 두고 있으며, 이후 북마크의 개수가 증가하면, 사용자는 북마크관리가 어렵게되므로 사용자 북마크 파일을 자동으로 분류하여 관리할수 있는 에이전트 기술을 사용하고자 한다. 대표적인 분류에이전트 시스템으로는 전자우편 분류 에이전트인 Maxims, 뉴스기사 분류 에이전트인 NewT, 엔터테인먼트(Entertainment) 선별 에이전트인 Ringo 등이 있다. 이러한 시스템들은 분류할 대상에 따라 조금씩 다른 모습의 에이전트 기능을 보이고 있으며, 본 논문은 기계학습 이론중 교사학습 알고리즘인 나이브 베이지안 학습방법(Naive Bayesian Learning method)을 사용하여 사용자가 분류하지 못한 북마크를 자동으로 분류하는 단일 에이전트 기반 북마크 분류기를 설계, 구현하고자한다.

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