• 제목/요약/키워드: 이용자 검색 키워드 분석

검색결과 34건 처리시간 0.023초

A Relation Analysis between NDSL User Queries and Technical Terms (NDSL 검색 질의어와 기술용어간의 관계에 대한 분석적 연구)

  • Kang, Nam-Gyu;Cho, Min-Hee;Kwon, Oh-Seok
    • Journal of Information Management
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    • 제39권3호
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    • pp.163-177
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    • 2008
  • In this paper, we analyzed the relationship between user query keywords that is used to search NDSL and technical terms extracted from NDSL journals. For the analysis, we extracted about 833,000 query keywords from NDSL search logs during nearly 17 months and approximately 41,000,000 technical terms from NDSL, INSPEC, FSTA journals. And we used only the English noun phrase in extracted those and then we did an experiment on analysis of equality, relationship analysis and frequency analysis.

Analysis of Keyword-based Content Search Service Requirements in Video Archive for Media Creation (미디어 창작을 위한 비디오 아카이브 키워드기반 내용 검색 서비스 요구사항 분석)

  • Jung, Byunghee;Park, Wan;Lee, Yunseong;Lee, Hajoo;Kim, Sansung
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 한국방송∙미디어공학회 2022년도 하계학술대회
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    • pp.1265-1267
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    • 2022
  • 방대한 분량의 콘텐츠 홍수 속에서 원하는 소재를 찾기 위해 콘텐츠 내용을 검색할 수 있는 효과적인 방법이 지원되는 것은 창작을 자유롭게 하고, 콘텐츠 활용도를 높이기 위해 매우 중요하다. KBS 바다 서비스의 경우 분류체계 방법을 사용하고 있으나. 최근 딥러닝을 이용한 인공지능 기술의 발전으로 콘텐츠의 내용을 인공지능 기술로 태깅하고, 태깅된 텍스트 정보를 이용하여 검색할 수 있는 기술 개발이 활발히 수행되고, 국가적으로도 해당 기술을 지원하고 있다. 본 논문에서는 이러한 기술 개발의 선행 요소인 방송사의 제작과정에서 요구되는 동영상 소재 콘텐츠 검색의 요구사항을 KBS 비디오 아카이브 검색 키워드 실제 사용 데이터를 이용하여 분석하였다. 약 1,000여건의 검색 키워드 분석과 이용자와 운영자의 응답 내용을 고찰한 결과, 특정 키워드에 집중하여 검색할 수 있도록 보완하여 주는 것이 필요함을 알아내었다. 또한, 검색 범위를 효과적으로 축소하여 검색을 손쉽고 빠르게 할 수 있는 방법을 고찰하였다. 본 논문에서는 미디어 창작에서 필요한 소재 콘텐츠를 찾기 위해 연구 개발해야 할 미디어 속성 추출 기술의 방향성을 제시하였다.

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Knowledge Level of Users of Keyword/Boolean Searching on an Online Public Access Catalog : SELIS (OPAC에 있어서 키워드/불연산자 탐색에 대한 이용자 지식수준 연구)

  • Koo Bon-Young
    • Journal of the Korean Society for Library and Information Science
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    • 제32권4호
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    • pp.249-274
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    • 1998
  • It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

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A Study on the Social and Cultural Characteristics of Web Queries (웹 검색질의어 분석을 통한 사회·문화적 특성에 관한 연구)

  • Kim, Seong-Hee
    • Journal of Information Management
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    • 제42권4호
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    • pp.155-174
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    • 2011
  • This study aims to focus on classifying the search engine queries according to web query topic and the different user intents behind web queries. First, we classified 10,000 web query data set by topic. The results showed that there was significant differences in interesting topics across time. Also, we categorized 500 popular queries in web search engine as informational, navigational, or transactional. As a result, 82 percent of web queries are informational in nature, with about 10.8 percent for navigational and 7.2 percent for transactional. This results will help establish the policy to provide internet contents based on user's intent and also find out the social and cultural characteristics.

Forecasting Open Government Data Demand Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 공공데이터 수요 예측)

  • Lee, Jae-won
    • Informatization Policy
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    • 제27권4호
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    • pp.24-46
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    • 2020
  • This study proposes a way to timely forecast open government data (OGD) demand(i.e., OGD requests, search queries, etc.) by using keyword network analysis. According to the analysis results, most of the OGD belonging to the high-demand topics are provided by the domestic OGD portal(data.go.kr), while the OGD related to users' actual needs predicted through topic association analysis are rarely provided. This is because, when providing(or selecting) OGD, relevance to OGD topics takes precedence over relevance to users' OGD requests. The proposed keyword network analysis framework is expected to contribute to the establishment of OGD policies for public institutions in the future as it can quickly and easily forecast users' demand based on actual OGD requests.

A Study on Analysis of Requirements and Design of IR System for Semantic-based Information Retrieval (시멘틱 검색시스템 구축을 위한 요구사항 분석 및 설계에 관한 연구)

  • Kim, Yong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • 제23권1호
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    • pp.91-111
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    • 2012
  • With the rapid expansion of web information, conventional information retrieval techniques are becoming inadequate for users and often result in disappointment, because a couple of simple keywords can easily produce information too much. This study aims at the development of Web information retrieval techniques based on semantics to improve the quality of understanding for information. To achieve the goal, this study analyzes technologies and current status of researches on semantic information retrieval. With the results which are requirements, system architecture and indexing method, this study proposes the system architecture of semantic-based information retrieval system.

Improving Twitter Search Function Using Twitter API (트위터 API를 활용한 트위터 검색 기능 개선)

  • Nam, Yong-Wook;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • 제8권3호
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    • pp.879-886
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    • 2018
  • The basic search engine on Twitter shows not only tweets that contain search keywords, but also all articles written by users with nicknames containing search keywords. Since the tweets unrelated to the search keyword are exposed as search results, it is inconvenient to many users who want to search only tweets that include the keyword. To solve this inconvenience, this study improved the search function of Twitter by developing an algorithm that searches only tweets that contain search keywords. The improved functionality is implemented as a Web service using ASP.NET MVC5 and is available to many users. We used a powerful collection method in C# to retrieve the results of an object, and it was also possible to output them according to the number of 'retweets' or 'favorites'. If the number of retrieved numbers is less than a given number, we also added an exclusion filter function. Thus, sorting search results by the number of retweets or favorites, user can quickly search for opinions that are of interest to many users. It is expected that many users and data analysts will find the developed function convenient to search on Twitter.

The Impact of OPAC Usability on User Satisfaction and Loyalty in University Library (대학도서관의 OPAC 유용성이 이용자의 만족도와 충성도에 미치는 영향)

  • Kim, Mi-Hye;Lee, Changsoo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • 제24권1호
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    • pp.5-24
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    • 2013
  • OPAC is a very important interface for user to use and search library collection and electronic resources. The purpose of this study is to analyze empirically the impact of OPAC usability on user satisfaction and loyalty in an university library setting. The OPAC functions investigated are keyword searching, integrated searching, faceted navigation, relevance ranking, spelling check, recommendations, user participation, and Really Simple Syndication(RSS), etc. This study investigated what usability effects on user satisfaction and loyalty and suggested the way to improve user satisfaction and loyalty.

A Study on the Improvement of Accessibility to Public Records: Based on the Construction of Subject Thesaurus for Presidential Archives (공공기록에 대한 접근성 제고 방안에 관한 연구 - 대통령기록관 주제시소러스 개발 사례를 중심으로 -)

  • Rieh, Hae-Young;Kwon, Yongchan;Seong, Hyojoo;Yoo, Byonghoo
    • Journal of Korean Society of Archives and Records Management
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    • 제14권4호
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    • pp.127-151
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    • 2014
  • To search based on the functional classification or provenance is not easy for users, and the key word-based information retrieval presents only simple words matching with the title of the records. The Presidential Archive of Korea developed a subject classification scheme to improve the convenience of searching for various records and came up with a subject thesaurus based on the scheme that utilizes the terms appearing on the title of the records and the terms used by the users who searched the portal or requested information disclosure. This research presents the development process of subject thesaurus. It also presents the utilization methods for records management work and services.

A Study on the Search Behavior of Digital Library Users: Focus on the Network Analysis of Search Log Data (디지털 도서관 이용자의 검색행태 연구 - 검색 로그 데이터의 네트워크 분석을 중심으로 -)

  • Lee, Soo-Sang;Wei, Cheng-Guang
    • Journal of Korean Library and Information Science Society
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    • 제40권4호
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    • pp.139-158
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    • 2009
  • This paper used the network analysis method to analyse a variety of attributes of searcher's search behaviors which was appeared on search access log data. The results of this research are as follows. First, the structure of network represented depending on the similarity of the query that user had inputed. Second, we can find out the particular searchers who occupied in the central position in the network. Third, it showed that some query were shared with ego-searcher and alter searchers. Fourth, the total number of searchers can be divided into some sub-groups through the clustering analysis. The study reveals a new recommendation algorithm of associated searchers and search query through the social network analysis, and it will be capable of utilization.

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