• 디지털콘텐츠학회 논문지
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• 제19권4호
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• pp.719-729
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• 2018

2017년 기준, 데스크탑과 모바일 영역에서 90% 이상의 압도적인 점유율을 보이는 검색엔진은 Google로써, 대다수의 사람들은 Google 이 검색하는 영역이 웹의 전체라고 생각할 것이다. 그러나 웹 연구 결과에 의하면 전체 웹 데이터의 불과 10% 만이 Google에 의해 검색가능하다고 한다. 대부분의 영역은 딥 웹이라고 불리며 Google 과는 다른 종류의 검색엔진들에 의해 검색된다. 해당 엔진들은 자신만의 딥 웹 데이터베이스를 구축 후 특화된 알고리즘을 사용하여 높은 정확성과 전문성의 검색결과를 제공한다. 현재 사용되고 있는 검색엔진들 중, 전체 웹 영역을 검색하는 엔진은 존재하지 않는다. 광범위에 걸쳐 그리고 유효하면서 정확 신속한 검색을 수행하기 위한 최적의 방법은 Google 같은 일반적인 검색엔진과 딥 웹 검색엔진들을 동시에 적용하여 결과를 도출하는 것이다. 본 논문에서는 이러한 검색엔진을 하이브리드검색엔진이라 명하고 기존 검색엔진들에 비해 갖는 차이점 및 특징에 대해 살펴본 후 개괄적인 프레임을 제시한다.

• 복식문화연구
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• 제9권3호
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• pp.412-432
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• 2001

Internet search engines are used by the majority of find information on the Web. However, Web users can be often dissatisfied with the mistakes in the retrieval of ‘Fashion’ information from the Internet. The purpose of this study is to analyze the ‘Fashion’ category structure in the Internet search engines. There are 2 steps for achieving it: the first, to investigate the structures of ‘Fashion’ categories and then, to analyze the gap between ‘Fashion’ categories defined by them and extensive ‘Fashion’categories, which are approached on 2 sides of the fashion-life and fashion-business. We select 5 major search engines for the case study: Yahoo, Lycos, Naver, Hanmir, Empas, which ranked as top 5 of total search engines and potal sites in February, 2001, and retrieve ‘Fashion’ categories from the first level to the last level by using both “topics retrieval”. Eventually, we can find the problems of ‘Fashion’ category structure in search engines. Also, it is concluded with a brief perspective of ‘Fashion’ categories in the Internet search engines and the implications for the future.

• 정보관리연구
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• 제31권4호
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• pp.50-70
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• 2000

인터넷으로 접근할 수 정보의 형태가 텍스트는 물론 이미지나 사운드까지 포함되면서 다양한 웹 이미지 검색엔진들이 개발되고 있다. 그러나 이 검색엔진들은 검색 특성과 효율성 면에서 상당한 차이를 보이고 있다. 이에 본 연구에서는 현재 개발된 이미지정보를 탐색하는 검색엔진들의 유형을 살펴보고 이들의 특성과 성능을 비교 평가하여 이용자로 하여금 정보요구에 적합한 이미지 검색엔진을 선택할 수 있도록 하는데 그 목적이 있다. 본 연구의 비교대상 검색엔진으로는 현재 가장 널리 쓰이고 있는 AV Photo Finder, Lycos MultiMedia, Amazing Picture Machina Image Surfer, WebSeek, Ditto를 선정하였다. 먼저 문헌연구를 통해 이미지 검색엔진의 평가기준을 마련하였다. 그리고 마련된 기준에 따라 각 검색엔진들의 데이터베이스 및 색인 방법, 검색 기능, 출력 형태, 이용자 인터페이스를 조사하였고 검색성능을 평가하기 위해 상대적 재현율과 정확률을 측정하였다. 그 결과 AV Photo Finder의 정확률이 가장 높았고 Ditto와 WebSeek의 정확률은 비교적 높은 편이었다. 그리고 Lycos MultiMedia와 Image Surfer의 정확률 값이 그 뒤를 이었으며 Amazing Picture Machine의 정확율이 가장 낮았다.

• 디지털산업정보학회논문지
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• 제4권1호
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• pp.1-8
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• 2008

In the Web 2.0, besides more gaining information on the web, the number of web sites that take advantage of RSS increases explosively. Commonly each users search RSS channels through the web search engine before registering RSS channel's url to the RSS reader. Users judge whether the site is RSS channel or not and register an RSS channel's url through theirs interests. Because accomplished by users themselves, those processes conflict to user's convenience and quick consumption of information. Techniques of current search engines can't provide users with reliable RSS feed information as search results. In this paper, we analysis appropriateness of current search engines' techniques that offer users RSS feed search service and discuss their limitations. Also, we make up RSS feed database through classification of RSS tag being possible to search RSS feed information effectively and apply update rate of each RSS channel's feed to ranking algorithm providing more reliable search results.

• 대한산업공학회지
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• 제39권2호
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• pp.119-128
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• 2013

Most internet users utilize internet portal search engines, such as Naver, Daum and Google nowadays. But since the results of internet portal search engines are based on universal criteria (e.g. search frequency by region or country), they do not consider personal interests. Namely, current search engines do not provide exact search results for homonym or polysemy because they try to serve universal users. In order to solve this problem, this research determines keyword importance and weight value for each individual search characteristics by collecting and analyzing customized keyword at external database. The customized keyword weight values are integrated with search engine results (e.g. PageRank), and the search ranks are rearranged. Using 50 web pages of Goolge search results for experiment and 6 web pages for customized keyword collection, the new customized search results are proved to be 90% match. Our personalization approach is not the way that users enter preference directly, but the way that system automatically collects and analyzes personal information and then reflects them for customized search results.

• 정보기술과데이타베이스저널
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• 제6권1호
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• pp.27-46
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• 1999

This study was intended to find the use patterns of internet search engines of librarians and to measure the relationship between internet use frequency and the use behavior of internet search engines. The results showed that librarians use Web search engines for academic information retrieval and are satisfied with the search results. The major problems when librarians use search engines were that search engines retrieve many non-relevant documents. As a result of hypotheses test, the relationship between internet frequency and the preference of search engines was not significantly different. On the other hand, the hypotheses that internet frequency affects satisfaction of search results, recognition of importance of search engines, and the need of retraining of librarians for internet information retrieval were shown to be significant.

• 한국도서관정보학회지
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• 제27권
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• pp.457-483
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• 1997

This study was intended to compare the effectiveness of the Savvy search and Metacrawler in terms of the total number of relevant documents retrieved, precision, recall, and the number of deadlines. In addition, this study measured whether the Meta-search engine and general web search engines retrieved different web documents. As a result, Savvy search produced a higher precision and recall as compared with motacrawler search engine while the metacrawler had lower deadlines ration than savvy search, Also, Meta search engine was more effective than the general web search engine, The results show that the hybrid methodology of integrating a variety of web search engines can help solve retrieval effectiveness problems on the Internet.

• 정보관리학회지
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• 제21권2호
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• pp.89-106
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• 2004

웹 상의 의학 분야 자료들은 방대한 규모로 존재하며, 각 검색엔진에서는 이를 분류하여 제공하고 있으나 그 구성에 있어서 일관성과 체계성이 부족하다. 따라서 본 논문은 검색엔진에서 의학 분야 웹 자료 분류체계를 구성하기 위하여 의학 전문 문헌분류표인 NLMC를 준용하고, 항목의 배열이 주제간 관련성을 기반으로 이루어져야 한다는 것을 제안하였다. 또한 순환성을 고려한 1차 분류 및 2차 분류 항목에서의 중복 분류시, 그에 대한 명확한 기준이 설정되어야 하며, 분류 항목명을 의학 분야 표준 용어집인 MeSH와 $\boxDr$의학용어집$\boxUl$의 용어로 선택하여 기존의 도서관 정보검색시스템과의 상호호환성을 높여야 한다는 것을 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2468-2487
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• 2015

In web searching, trustable and precise results are greatly affected by the inherent uncertainty in the input queries. Queries submitted to search engines are by nature ambiguous and constitute a significant proportion of the instances given to web search engines. Ambiguous queries pose real challenges for the web search engines due to versatility of information. Temporal based approaches whereas somehow reduce the uncertainty in queries but still lack to provide results according to users aspirations. Web search science has created an interest for the researchers to incorporate contextual information for resolving the uncertainty in search results. In this paper, we propose an Adaptive Disambiguation Approach (ADA) of hybrid nature that makes use of both the temporal and contextual information to improve user experience. The proposed hybrid approach presents the search results to the users based on their location and temporal information. A Java based prototype of the systems is developed and evaluated using standard dataset to determine its efficacy in terms of precision, accuracy, recall, and F1-measure. Supported by experimental results, ADA demonstrates better results along all the axes as compared to temporal based approaches.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2002년도 추계정기학술대회
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• pp.266-272
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• 2002

Recently various of information suppliers provide information via WWW so the necessary of search engine grows larger. However the efficiency of most search engines is low comparatively because of using simple pattern match technique between user's query and web document. And a manifest contents of query for special expert field so much worse A specialized search engine returns the specialized information depend on each user's search goal. It is trend to develop specialized search engines in many countries. For example, in America, there are a site that searches only the recently updated headline news and the federal law and the government and and so on. However, most such engines don't satisfy the user's needs. This paper proposes the specialized search engine for ocean information that uses user's query related with ocean and search engine uses the association rules in web data mining. So specialized search engine for ocean provides more information related to ocean because of raising recall about user's query