• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.203-225
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• 2004

This study is to investigate the characteristics of the Invisible Web and many search services designed to serve as gateways to the Invisible Web and to evaluate searching the Invisible Web in the Services. The four services for searching the Invisible Web were selected to search the Invisible Web with 11 queries, that are Google as portals, ProFusion and Search.com as Invisible Web meta search engines, and IncyWincy as Invisible Web search engines. It was found that the effectiveness of Google's Invisible Web searching was better compared with the three Invisible Web search tools but the difference between the four systems was not significant((${\alpha}$=.055) The Invisible Web meta searching was better than the Web meta searching in the three search tools at the statistically significant level. The effectiveness measurement based on the ranks and relevance degree(quality) of relevant documents retrieved seemed appropriate to the ranked search results.

• Journal of Korean Library and Information Science Society
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• v.31 no.1
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• pp.87-114
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• 2000

The purpose of this study is offering appropriate system and training program to helf the system designer and the trainer in addition to analyze information use behavior about the web search tools and evaluate the estimated system by user groups. The results of the study are as follows $\circledS1$ It is desirable to consider age than other demographic variables in the case of web search tool. $\circledS2$ It is desirable to design Directory Search Tool in the case of web search tool which serves the student user group. $\circledS3$ An Intelligent Search Tool is more appropriate for the students who are using keyword search tool than any other tools. $\circledS4$ A discussion about standard classification of the web information should be accomplished soon because users feel confused in using web search tools due t o absence of standard mode of classification about classified item. $\circledS5$ Librarians need the cognition about data on internet s a source of information and need positive service and user training program about these information because student users hardly get help from librarians or library orientation for learning method to use web search tool. $\circledS6$ Internet use experience and years of computer use had effect on their use ability when using web search tool, whereas computer use experience, library use experience and Online Public Access Catalogs (OPAC) use experience had no effect on it. Especially, OPAC use experience had no effect on use ability of web search tool of student user group because student user groups had no information about internet and web search tool and they did not recognized the difference about search method between web search tool and OPAC. $\circledS7$In the case of web search tool, it si important to index the increasing web resource automatically by a searching robot. But in the case of student users, web search tool is much more needed to index by index expert due to the absence of ability about selecting and combining keyword.

• Journal of Sasang Constitutional Medicine
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• v.27 no.4
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• pp.388-395
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• 2015

Objectives To grasp the trend of constitution medical industry related to the metabolic disorders by analyzing the web resource.Methods Web search with the search formula ("constitutional" or "spirit") and ("Metabolic" or "diabetes" or "high blood pressure" or "hyperlipidemia" or "obesity") for 20 years (1995.09.10 ~ 2015.09.09.) in the web portal address "Web search with the search formula ("constitutional" or "spirit") and ("Metabolic" or "diabetes" or "high blood pressure" or "hyperlipidemia" or "obesity") for 20 years (1995.09.10 ~ 2015.09.09.) in the web portal address "http://web.search.naver.com".Results In the search area of news, blogs, cafes and knowledge-in, the number of searched pages retrieved by the word "constitution" was about 1.78 million. In the news 9760 cases of "obesity", 4046 cases of "hypertension" and 3253 cases of "diabetes" were searched. In Naver Web search Korean medicine clinics related to "constitution" were 24.3%. If we multiple 25.3% to 1000, the actual number of herbal hospitals, The constitution related to Korean medicine clinics is estimated to be approximately 3160 places. Among metabolic disorders, "Overweight", "Diabetes" and "Hypertension" were most frequently searched.Conclusions Constitutional industry related to metabolic diseases is very actively created on the internet in various areas. Among metabolic diseases, obesity, diabetes, hypertension were found with high frequency.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.238-240
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• 2004

정보 통신 기술의 발달로 엄청난 양의 정보가 World Wide Web을 통해 저장되고 공유된다. 특히, 사용자가 WWW을 이용하여 필요한 정보를 얻고자할 때, 가장 많이 사용되는 것이 Web search engine이다. 그러나 Web search engine의 algorithm 자체의 부정확성과 악의적으로 작성된 Web page로 인해 search engine 결과가 사용자의 요구와 일치하지 못하는 문제가 발생한다. 본 논문에서는 여러 Web search algorithm 중에서 Web structure management 기법을 중심으로 문제점을 분석하고 이를 해결할 수 있는 수정된 algorithm을 제시한다. 마지막으로 제시된 algorithm이 spamming page를 filtering하는 과정을 예시하여 논증한다.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.27-34
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• 2010

Web crawlers are fundamental programs which iteratively download web pages by following links of web pages starting from a small set of initial URLs. Previously several web crawling orderings have been proposed to crawl popular web pages in preference to other pages, but some graph search techniques whose characteristics and efficient implementations had been studied in graph theory community have not been applied yet for web crawling orderings. In this paper we consider various graph search techniques including lexicographic breadth-first search, lexicographic depth-first search and maximum cardinality search as well as well-known breadth-first search and depth-first search, and then choose effective web crawling orderings which have linear time complexity and crawl popular pages early. Especially, for maximum cardinality search and lexicographic breadth-first search whose implementations are non-trivial, we propose linear-time web crawling orderings by applying the partition refinement method. Experimental results show that maximum cardinality search has desirable properties in both time complexity and the quality of crawled pages.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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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.

• The KIPS Transactions:PartD
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• v.15D no.3
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• pp.305-312
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• 2008

Web documents with useful information are widely available on the internet and they are accessible with web search service. For this reason, web search services study better ways to collect more web documents, but have a difficulty figuring out the coverage of these web pages. This paper is intended to find ways to evaluate the current coverage assessment methods and suggest more effective coverage assessment technique that is, sampling internet web documents equally, monitoring how they are classified on web search services, in an attempt to assess both absolute and relative coverage of the web search engines. The paper also presents the comparison among Korean web search services using the suggested methods.the absolute and relative coverage was highest in Google followed by Naver and Empas. The result is expected to help estimating coverage of web search services.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.719-729
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• 2018

Abstract In 2017, it has been reported that Google had more than 90% of the market share in search-engines of desktops and mobiles. Most people may consider that Google surely searches the entire web area. However, according to many researches for web data, Google only searches less than 10%, surprisingly. The most region is called the Deep Web, and it is indexable by special search engines, which are different from Google because they focus on a specific segment of interest. Those engines build their own deep-web databases and run particular algorithms to provide accurate and professional search results. There is no search engine that indexes the entire Web, currently. The best way is to use several search engines together for broad and efficient searches as best as possible. This paper defines that kind of search engine as Hybrid Search Engine and provides characteristics and differences compared to conventional search engines, along with a frame of hybrid search engine.

• The KIPS Transactions:PartD
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• v.16D no.5
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• pp.683-690
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• 2009

Social Networks which is composed of network with an individual in the center in a web support mutual-understanding of information by searching user profile and forming new link. Therefore, if we apply the Social Network which consists of web users who have similar immanent information to web search, we can improve efficiency of web search and satisfaction of web user about search results. In this paper, first, we make a Social Network using web users linked directly or indirectly. Next, we calculate Similarity among web users using their immanent information according to topics, and then reconstruct Social Network based on varying Similarity according to topics. Last, we compare Similarity with Search Pattern. As a result of this test, we can confirm a result that among users who have high relationship index, that is, who have strong link strength according to personal attributes have similar search pattern. If such fact is applied to search algorithm, it can be possible to improve search efficiency and reliability in personalized and social search.