• Title/Summary/Keyword: 키워드 추출 방법

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User Preference based Intelligent Program Guide (사용자 선호도 기반 지능형 프로그램 가이드)

  • 류지웅;김문철;남제호;강경옥;김진웅
    • Journal of Broadcast Engineering
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    • v.7 no.2
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    • pp.153-167
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    • 2002
  • With the advent of digital broadcasting, a large number of program channels become available at the user terminals such as set-top-box or PC. Channel navigation and searching become more difficult at TV terminal sides using a conventional device such as a TV remote controller. The MPEG-7 MDS (Multimedia Description Scheme) and TV Anytime set up a standard about how to describe user preferences for genre, channel, actor/actress, keyword, etc. of the TV programs, and how to describe usage history for user's program consumption behaviors and preferences. But they do not describe how to use them. In this paper, we describe an IPG (Intelligent Program Guider) system that provides TV program and channel information based on user preferences and suggest easy access to TV program that user wants. The IPG monitors user's behaviors of interacting to programs and automatically updates the user's preference changes according1y. The IPG utilizes user preferences description scheme specified in both MPEG-7 MDS and TV Anytime metadata specifications.

A Term Weight Mensuration based on Popularity for Search Query Expansion (검색 질의 확장을 위한 인기도 기반 단어 가중치 측정)

  • Lee, Jung-Hun;Cheon, Suh-Hyun
    • Journal of KIISE:Software and Applications
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    • v.37 no.8
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    • pp.620-628
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    • 2010
  • With the use of the Internet pervasive in everyday life, people are now able to retrieve a lot of information through the web. However, exponential growth in the quantity of information on the web has brought limits to online search engines in their search performance by showing piles and piles of unwanted information. With so much unwanted information, web users nowadays need more time and efforts than in the past to search for needed information. This paper suggests a method of using query expansion in order to quickly bring wanted information to web users. Popularity based Term Weight Mensuration better performance than the TF-IDF and Simple Popularity Term Weight Mensuration to experiments without changes of search subject. When a subject changed during search, Popularity based Term Weight Mensuration's performance change is smaller than others.

Video Retrieval System supporting Adaptive Streaming Service (적응형 스트리밍 서비스를 지원하는 비디오 검색 시스템)

  • 이윤채;전형수;장옥배
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.1
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    • pp.1-12
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    • 2003
  • Recently, many researches into distributed processing on Internet, and multimedia data processing have been performed. Rapid and convenient multimedia services supplied with high quality and high speed are to be needed. In this paper, we design and implement clip-based video retrieval system on the Web enviroment in real-time. Our system consists of the content-based indexing system supporting convenient services for video content providers, and the Web-based retrieval system in order to make it easy and various information retrieval for users in the Web. Three important methods are used in the content-based indexing system, key frame extracting method by dividing video data, clip file creation method by clustering related information, and video database construction method by using clip unit. In Web-based retrieval system, retrieval method ny using a key word, two dimension browsing method of key frame, and real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time display method of the clip are used. In this paper, we design and implement the system that supports real-time retrieval for video clips on Web environment and provides the multimedia service in stability. The proposed methods show a usefulness of video content providing, and provide an easy method for serching intented video content.

A Question Example Generation System for Multiple Choice Tests by utilizing Concept Similarity in Korean WordNet (한국어 워드넷에서의 개념 유사도를 활용한 선택형 문항 생성 시스템)

  • Kim, Young-Bum;Kim, Yu-Seop
    • The KIPS Transactions:PartA
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    • v.15A no.2
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    • pp.125-134
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    • 2008
  • We implemented a system being able to suggest example sentences for multiple choice tests, considering the level of students. To build the system, we designed an automatic method for sentence generation, which made it possible to control the difficulty degree of questions. For the proper evaluation in the multiple choice tests, proper size of question pools is required. To satisfy this requirement, a system which can generate various and numerous questions and their example sentences in a fast way should be used. In this paper, we designed an automatic generation method using a linguistic resource called WordNet. For the automatic generation, firstly, we extracted keywords from the existing sentences with the morphological analysis and candidate terms with similar meaning to the keywords in Korean WordNet space are suggested. When suggesting candidate terms, we transformed the existing Korean WordNet scheme into a new scheme to construct the concept similarity matrix. The similarity degree between concepts can be ranged from 0, representing synonyms relationships, to 9, representing non-connected relationships. By using the degree, we can control the difficulty degree of newly generated questions. We used two methods for evaluating semantic similarity between two concepts. The first one is considering only the distance between two concepts and the second one additionally considers positions of two concepts in the Korean Wordnet space. With these methods, we can build a system which can help the instructors generate new questions and their example sentences with various contents and difficulty degree from existing sentences more easily.

Design and Implementation of a Clip-Based Video Retrieval System Supporting Internet Services (인터넷 서비스를 지원하는 클립 기반 비디오 검색 시스템의 설계 및 구현)

  • 양명섭;이윤채
    • Journal of Internet Computing and Services
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    • v.2 no.1
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    • pp.49-61
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    • 2001
  • Internet has been becoming widely popular and making rapid progress and network technologies is showing extension in data transmission speeds. Rapid and convenient multimedia services supplied with high quality and high speed are being needed, This paper treats of the design and implement method of clip-based video retrieval system on the world-wide-web environments. The implemented system consists of the content-based indexing system supporting convenient services for video contents providers and the web-based retrieval system in order to make it easy and various information retrieval for users on the world-wide-web. Three important methods were used in the content-based indexing system. Key frame extracting method by dividing video data, clip file creation method by clustering related information and video database build method by using clip unit, In web-based retrieval system, retrieval method by using a key word, two dimension browsing method of key frame and real-time display method of the clip were used. As a result. the proposed methodologies showed a usefulness of video content providing. and provided an easy method for searching intented video content.

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A Study on Organizing the Web Using Facet Analysis (패싯 분석을 이용한 웹 자원의 조직)

  • Yoo, Yeong-Jun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.15 no.1
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    • pp.23-41
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    • 2004
  • In indexing and organizing Web resources, there have been two basic methods: automatic indexing by extracting key words and library classification schemes or subject directories of search engines. But, both methods have failed to satisfy the user's information needs, due to the lack of standard criteria and the irrationality of its structural system. In this paper I have examined the limits of library classification scheme's structures and the problems related to the nature of Web resources such as specificity and exhaustivity. I have also attempted to explain the logicality of Web resources organization by facet analysis and its strengths and limitations. In so doing, I have proposed three specific methods in using facet analysis: firstly, indexing system by facet analysis; secondly, the alternative transformation of the enumerative classification scheme into facet classification scheme; and finally, the facet model of subject directory of domestic search engine. After examining the three methods, my study concludes that a controlled vocabulary by facet analysis can be employed as a useful method in organizing Web resources.

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The Analysis of Changes in East Coast Tourism using Topic Modeling (토핑 모델링을 활용한 동해안 관광의 변화 분석)

  • Jeong, Eun-Hee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.6
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    • pp.489-495
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    • 2020
  • The amount of data is increasing through various IT devices in a hyper-connected society where the 4th revolution is progressing, and new value can be created by analyzing that data. This paper was collected total 1,526 articles from 2017 to 2019 in central magazines, economic magazines, regional associations, and major broadcasting companies with the keyword "(East Coast Tourism or East Coast Travel) and Gangwon-do" through Bigkinds. It was performed the topic modeling using LDA algorithm implemented in the R language to analyze the collected 1,526 articles. It was extracted keywords for each year from 2017 to 2019, and classified and compared keywords with high frequency for each year. It was setted the optimal number of topics to 8 using Log Likelihood and Perplexity, and then inferred 8 topics using the Gibbs Sampling method. The inferred topics were Gangneung and Beach, Goseong and Mt.Geumgang, KTX and Donghae-Bukbu line, weekend sea tour, Sokcho and Unification Observatory, Yangyang and Surfing, experience tour, and transportation network infra. The changes of articles on East coast tourism was was analyzed using the proportion of the inferred eight topics. As the result, the proportion of Unification Observatory and Mt. Geumgang showed no significant change, the proportion of KTX and experience tour increased, and the proportion of other topics decreased in 2018 compared to 2017. In 2019, the proportion of KTX and experience tour decreased, but the proportion of other topics showed no significant change.

A Study on Development of Patent Information Retrieval Using Textmining (텍스트 마이닝을 이용한 특허정보검색 개발에 관한 연구)

  • Go, Gwang-Su;Jung, Won-Kyo;Shin, Young-Geun;Park, Sang-Sung;Jang, Dong-Sik
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.8
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    • pp.3677-3688
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    • 2011
  • The patent information retrieval system can serve a variety of purposes. In general, the patent information is retrieved using limited key words. To identify earlier technology and priority rights repeated effort is needed. This study proposes a method of content-based retrieval using text mining. Using the proposed algorithm, each of the documents is invested with characteristic value. The characteristic values are used to compare similarities between query documents and database documents. Text analysis is composed of 3 steps: stop-word, keyword analysis and weighted value calculation. In the test results, the general retrieval and the proposed algorithm were compared by using accuracy measurements. As the study arranges the result documents as similarities of the query documents, the surfer can improve the efficiency by reviewing the similar documents first. Also because of being able to input the full-text of patent documents, the users unacquainted with surfing can use it easily and quickly. It can reduce the amount of displayed missing data through the use of content based retrieval instead of keyword based retrieval for extending the scope of the search.

A Generation and Matching Method of Normal-Transient Dictionary for Realtime Topic Detection (실시간 이슈 탐지를 위한 일반-급상승 단어사전 생성 및 매칭 기법)

  • Choi, Bongjun;Lee, Hanjoo;Yong, Wooseok;Lee, Wonsuk
    • The Journal of Korean Institute of Next Generation Computing
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    • v.13 no.5
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    • pp.7-18
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    • 2017
  • Recently, the number of SNS user has rapidly increased due to smart device industry development and also the amount of generated data is exponentially increasing. In the twitter, Text data generated by user is a key issue to research because it involves events, accidents, reputations of products, and brand images. Twitter has become a channel for users to receive and exchange information. An important characteristic of Twitter is its realtime. Earthquakes, floods and suicides event among the various events should be analyzed rapidly for immediately applying to events. It is necessary to collect tweets related to the event in order to analyze the events. But it is difficult to find all tweets related to the event using normal keywords. In order to solve such a mentioned above, this paper proposes A Generation and Matching Method of Normal-Transient Dictionary for realtime topic detection. Normal dictionaries consist of general keywords(event: suicide-death-loop, death, die, hang oneself, etc) related to events. Whereas transient dictionaries consist of transient keywords(event: suicide-names and information of celebrities, information of social issues) related to events. Experimental results show that matching method using two dictionary finds more tweets related to the event than a simple keyword search.

Semantic Topic Selection Method of Document for Classification (문서분류를 위한 의미적 주제선정방법)

  • Ko, kwang-Sup;Kim, Pan-Koo;Lee, Chang-Hoon;Hwang, Myung-Gwon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.1
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    • pp.163-172
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    • 2007
  • The web as global network includes text document, video, sound, etc and connects each distributed information using link Through development of web, it accumulates abundant information and the main is text based documents. Most of user use the web to retrieve information what they want. So, numerous researches have progressed to retrieve the text documents using the many methods, such as probability, statistics, vector similarity, Bayesian, and so on. These researches however, could not consider both the subject and the semantics of documents. As a result user have to find by their hand again. Especially, it is more hard to find the korean document because the researches of korean document classification is insufficient. So, to overcome the previous problems, we propose the korean document classification method for semantic retrieval. This method firstly, extracts TF value and RV value of concepts that is included in document, and maps into U-WIN that is korean vocabulary dictionary to select the topic of document. This method is possible to classify the document semantically and showed the efficiency through experiment.