• Title/Summary/Keyword: 태그 기반 정보검색

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Measuring Web Page Similarity using Tags (태그를 이용한 웹 페이지간의 유사도 측정 방법)

  • Kang, Sang-Wook;Lee, Ki-Yong;Kim, Hyeon-Gyu;Kim, Myoung-Ho
    • Journal of KIISE:Databases
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    • v.37 no.2
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    • pp.104-112
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    • 2010
  • Social bookmarking is one of the most interesting trends in the current web environment. In a social bookmarking system, users annotate a web page with tags, which describe the contents of the page. Numerous studies have been done using this information, mostly on enhancing the quality of web search. In this paper, we use this information to measure the semantic similarity between two web pages. Since web pages consist of various types of multimedia data, it is quite difficult to compare the semantics of two web pages by comparing the actual data contained in the pages. With the help of social bookmarks, this comparison can be performed very effectively. In this paper, we propose a new similarity measure between web pages, called Web Page Similarity Based on Entire Tags (WSET), based on social bookmarks. The experimental results show that the proposed measure yields more satisfactory results than the previous ones.

Music Recommendation based on Blog Keyword Extraction (블로그 키워드 추출을 통한 음악 추천 기법)

  • Choi, Hong-gu;Jun, Sanghoon;Hwang, Eenjun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.11a
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    • pp.701-704
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    • 2010
  • 본 논문에서는 블로그의 포스트로부터 주요 키워드를 추출하여 노래 가사 데이터와 유사도를 분석, 해당 블로그 포스트에 적합한 음악을 추천하는 기법을 제안한다. 또한, 블로거가 포스트마다 제시한 태그들도 주요한 키워드로서 활용한다. 이를 위해서, 첫째로 TF-IDF 기법을 사용하여 텍스트로 구성된 포스트의 중요 키워드를 추출한다. 둘째로 포스트의 태그와 추출된 키워드를 기반으로 유사한 노래 가사를 LSA 기법으로 검색하여 가장 높은 유사도를 갖는 음악을 선택, 적합한 음악으로써 추천한다. 사용자 만족도 평가 실험을 통해서 제안하는 기법이 실제 추천에 적합한지 검증한다.

Concept Network-based Personalized Web Search Systems (개념 네트워크 기반 사용자 인지형 웹 검색 시스템)

  • Yune, Hong-June;Noh, Joon-Ho;Kim, Han-Joon;Lee, Byung-Jeong;Kang, Soo-Yong;Chang, Jae-Young
    • Journal of Internet Computing and Services
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    • v.12 no.2
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    • pp.63-73
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    • 2011
  • In general, conventional search engines provide the same search results for the same queries of users, and however such techniques do not consider users' characteristics. To overcome this problem, we need a new way of personalized search which returns customized search results according to users' preference. In this paper, we propose a concept network profile-based personalized web search system in which the concept network is developed for accumulating users' characteristics. The concept network-based user profile is used to expand initial search queries to achieve personalized search. The concept network is a network structure of concepts where each concept is generated whenever each query is submitted, and it can be defined as a set of keywords extracted from the selected documents. Furthermore, we have improved the concept networks by augmenting intent keywords of each concept with a set of classification tags, called folksonomy, assigned to each document. For an additional personalized search technique, we propose a new re-ranking method that analayzes the degree of overlapped search results.

Discovering News Keyword Associations Using Association Rule Mining (연관규칙 마이닝을 활용한 뉴스기사 키워드의 연관성 탐사)

  • Kim, Han-Joon;Chang, Jae-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.6
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    • pp.63-71
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    • 2011
  • The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.

A Design and Implementation of RSS Data Collecting Engine based on Web 2.0 (웹 2.0 기반 RSS 데이터 수집 엔진의 설계 및 구현)

  • Kang, Pil-Gu;Kim, Jae-Hwan;Lee, Sang-Jun;Chae, Jin-Seok
    • Journal of Korea Multimedia Society
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    • v.10 no.11
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    • pp.1496-1506
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    • 2007
  • The environment of web service has changed a great deal due to the progress of internet technology and positive participation of users. The established web service is static and passive, but the recent web service is becoming dynamic and active. Web 2.0 reflects current web service change well. The primary feature of web 2.0 is positive participation of users. Since the size of generated information is becoming larger, it is highly required to share the information fast and correctly. The technology to satisfy this need is web syndication and tagging in web 2.0. The web syndication makes feeds for another site or users to receive the content of web site. In addition, the tagging is the kernel of a information. Many internet users share rapidly the information through tag search. In this paper, we propose the efficient technique to improve the web 2.0 technology such as web syndication and tagging by using the data collection engine. Data collection engine has stored in a database, a user's Web site to use the information. and it has a user's Web site with access to updated data to collect. The experimental results show that our approach can improve the search speed up to 3.14 times better than the existing method and reduce the size of data up to 66% for building associated tags.

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Automatic Genre Classification using Music Harmonic Detection (화성정보 추출을 이용한 음악 장르분류)

  • Son Woo-Ram;Jung Min-Seok;An Joo-Young;Yoon Kyoung-Ro
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06b
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    • pp.280-282
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    • 2006
  • 저장매체의 대용량화와 인터넷을 이용한 디지털 음원의 활성화로 개인이 소유하는 음원이 급속도로 증가하고 있다. 많은 양의 음원을 보유하고 있는 상황에서 사용자의 편의를 증가시키기 위하여 다양한 검색/분류 방법들이 개발되고 사용되고 있다. 본 논문에서는 음원에 사용된 표현방식이나 디렉토리 구조, 파일이름, 텍스트 태그 등에 독립적으로 적용될 수 있도록 디지털 신호처리 이론에 기반하여 파형데이터를 분석하고, 화성학 이론에 기반한 패턴매칭 기술을 응용하여 음악의 장르와 나아가 분위기를 기반으로 분류하는 방법을 제시한다.

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Similarity checking between XML tags through expanding synonym vector (유사어 벡터 확장을 통한 XML태그의 유사성 검사)

  • Lee, Jung-Won;Lee, Hye-Soo;Lee, Ki-Ho
    • Journal of KIISE:Software and Applications
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    • v.29 no.9
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    • pp.676-683
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    • 2002
  • The success of XML(eXtensible Markup Language) is primarily based on its flexibility : everybody can define the structure of XML documents that represent information in the form he or she desires. XML is so flexible that XML documents cannot be automatically provided with an underlying semantics. Different tag sets, different names for elements or attributes, or different document structures in general mislead the task of classifying and clustering XML documents precisely. In this paper, we design and implement a system that allows checking the semantic-based similarity between XML tags. First, this system extracts the underlying semantics of tags and then expands the synonym set of tags using an WordNet thesaurus and user-defined word library which supports the abbreviation forms and compound words for XML tags. Seconds, considering the relative importance of XML tags in the XML documents, we extend a conventional vector space model which is the most generally used for document model in Information Retrieval field. Using this method, we have been able to check the similarity between XML tags which are represented different tags.

A Study on Layout Extraction from Internet Documents Through Xpath (Xpath에 의한 인터넷 문서의 레이아웃 추출 방법에 관한 연구)

  • Han Kwang-Rok;Sun Bok-Keun
    • The Journal of the Korea Contents Association
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    • v.5 no.4
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    • pp.237-244
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    • 2005
  • Currently most Internet documents including news data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of web pages by identifying the characteristics and structure of block tags that affect the layout of web pages and calculating distances between web pages. As a result of experiment, we can successfully extract 640 documents from 1000 samples and obtain 64% recall rate. This method is purposed to reduce the cost of web document automatic processing and improve its efficiency through applying the method to document preprocessing of information retrieval such as data extraction and document summarization.

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An Implementation and Application Of HTML Text Editor Using Problem-Based Learning (PBL 기반 HTML 텍스트 에디터 구현 및 적용)

  • Lee, Eun-Young;Kim, Kap-Su
    • 한국정보교육학회:학술대회논문집
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    • 2007.01a
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    • pp.197-202
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    • 2007
  • 컴퓨터 관련 인프라가 양적으로 팽창하는 지식 정보화 사회에서 컴퓨터 교육은 기초 기본 교육과 더불어 필수적으로 이루어져야 한다. 본 논문에서는 학생들이 쉽게 그리고 많이 접하는 웹에 관한 내용을 지도함에 있어 단순히 인터넷 검색이 아니라 어떻게 웹 페이지가 만들어지는지에 초점을 두었다. 이를 위해 PBL기반 HTML 텍스트 에디터를 구현하고 이를 수업에 직접 적용하여 배운 내용에 관한 형성 평가와 HTML 수업에 대한 흥미나 관심도 등을 설문지를 통해 알아보았다. 실험 결과 실험 집단과 통제 집단 사이에서 에디터로 인한 형성평가 성취도에는 차이가 없었다. 설문지를 통해 조사한 정의적인 영역은 7문항 중 수업의 난이도를 질문한 문항과 앞으로 홈페이지를 만들 수 있는가를 질문한 문항에서만 유의미한 차이를 보였다. PBL 기반의 HTML 텍스트 에디터는 인지적 영역의 성취도에서는 큰 차이를 보이지 않지만 직접 HTML 태그를 치지 않는 에디터를 이용해도 HTML과 관련된 지식을 습득할 수 있음을 보여준다.

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A Lifelog Management System Based on the Relational Data Model and its Applications (관계 데이터 모델 기반 라이프로그 관리 시스템과 그 응용)

  • Song, In-Chul;Lee, Yu-Won;Kim, Hyeon-Gyu;Kim, Hang-Kyu;Haam, Deok-Min;Kim, Myoung-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.9
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    • pp.637-648
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    • 2009
  • As the cost of disks decreases, PCs are soon expected to be equipped with a disk of 1TB or more. Assuming that a single person generates 1GB of data per month, 1TB is enough to store data for the entire lifetime of a person. This has lead to the growth of researches on lifelog management, which manages what people see and listen to in everyday life. Although many different lifelog management systems have been proposed, including those based on the relational data model, based on ontology, and based on file systems, they have all advantages and disadvantages: Those based on the relational data model provide good query processing performance but they do not support complex queries properly; Those based on ontology handle more complex queries but their performances are not satisfactory: Those based on file systems support only keyword queries. Moreover, these systems are lack of support for lifelog group management and do not provide a convenient user interface for modifying and adding tags (metadata) to lifelogs for effective lifelog search. To address these problems, we propose a lifelog management system based on the relational data model. The proposed system models lifelogs by using the relational data model and transforms queries on lifelogs into SQL statements, which results in good query processing performance. It also supports a simplified relationship query that finds a lifelog based on other lifelogs directly related to it, to overcome the disadvantage of not supporting complex queries properly. In addition, the proposed system supports for the management of lifelog groups by providing ways to create, edit, search, play, and share them. Finally, it is equipped with a tagging tool that helps the user to modify and add tags conveniently through the ion of various tags. This paper describes the design and implementation of the proposed system and its various applications.