• Title/Summary/Keyword: Web search engines

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A Study on the Motivation and User Satisfaction of Medical Students Using the Academic Search Engines (의과대학 대학원생의 학술정보 검색엔진 이용 동기 및 이용자 만족도에 관한 연구)

  • Shim, Saebom;Yi, Yongjeong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.30 no.4
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    • pp.197-216
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    • 2019
  • The study aimed to investigate the motivation and user satisfaction of medical school graduate students using specific academic information sites, and examines the effect of usage motivation factors on user satisfaction. This study was conducted from September 10, 2018 to September 21, 2018 by a large medical school graduate student in Seoul, and analyzed 135 valid responses. According to the analysis, the degree of reliability and interactivity of PubMed is higher than that of Google Scholar in medical school graduate students' use of academic information sites. It was found to have a significant effect on user satisfaction of academic information sites. In particular, convenience has the greatest influence on users' choice of academic information sites. The results of the study are of theoretical implications in that the discussion of academic information services through web sites is explained in terms of use and satisfaction in the context of medical information. On the other hand, specific research results provide practical implications for improving the services of medical-related academic search engines.

Quality Dimensions Affecting the Effectiveness of a Semantic-Web Search Engine (검색 효과성에 영향을 미치는 시맨틱웹 검색시스템 품질요인에 관한 연구)

  • Han, Dong-Il;Hong, Il-Yoo
    • Asia pacific journal of information systems
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    • v.19 no.1
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    • pp.1-31
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    • 2009
  • This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.

Mash-up System for Searching Herb using Herb Ontology (약재 온톨로지를 활용한 약재 검색 매쉬업 시스템)

  • Kim, Sang-Kyun;Kim, Chul;Jang, Hyun-Chul;Yea, Sang-Jun;Song, Yea.Mi-Young
    • Journal of Information Management
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    • v.39 no.4
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    • pp.173-186
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    • 2008
  • We propose a mash-up system for searching herb, which can search the herbal information in oriental medicine fields using the various Open APIs. We in particular developed and opened two Open APIs which enable to search papers and projects in oriental medicine fields with the general Open APIs. These Open APIs can share and provide the expert knowledge in oriental medicine fields. The information for a herb in oriental medicine fields has various names and descriptions according to their sources unlike other fields. Thus, it is hard to get the results using one or two keywords such as the general search engines. To solve this problem, we in this paper propose a way to provide the more exact and extensive search results using the herb ontology with one hundred herbal information in oriental medicine fields.

Ranking Quality Evaluation of PageRank Variations (PageRank 변형 알고리즘들 간의 순위 품질 평가)

  • Pham, Minh-Duc;Heo, Jun-Seok;Lee, Jeong-Hoon;Whang, Kyu-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.46 no.5
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    • pp.14-28
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    • 2009
  • The PageRank algorithm is an important component for ranking Web pages in Google and other search engines. While many improvements for the original PageRank algorithm have been proposed, it is unclear which variations (and their combinations) provide the "best" ranked results. In this paper, we evaluate the ranking quality of the well-known variations of the original PageRank algorithm and their combinations. In order to do this, we first classify the variations into link-based approaches, which exploit the link structure of the Web, and knowledge-based approaches, which exploit the semantics of the Web. We then propose algorithms that combine the ranking algorithms in these two approaches and implement both the variations and their combinations. For our evaluation, we perform extensive experiments using a real data set of one million Web pages. Through the experiments, we find the algorithms that provide the best ranked results from either the variations or their combinations.

Development of Yóukè Mining System with Yóukè's Travel Demand and Insight Based on Web Search Traffic Information (웹검색 트래픽 정보를 활용한 유커 인바운드 여행 수요 예측 모형 및 유커마이닝 시스템 개발)

  • Choi, Youji;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.23 no.3
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    • pp.155-175
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    • 2017
  • As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

Evaluation for Food and Nutrition Information Sites on the Internet (식품영양정보 제공 인터넷 사이트 평가)

  • Bae, Hyeon-Ju;Park, Hae-Jeong;Chae, Mi-Jin;Yun, Eun-Yeong;Kim, Gyeong-Won;Seo, Jeong-Suk
    • Journal of the Korean Dietetic Association
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    • v.12 no.4
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    • pp.404-410
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    • 2006
  • This study was done to analyze the contents of food and nutrition information sites on the internet. In analysis, 276 web sites were used. Web sites from 3 internet search engines(Yahoo, Empas, Naver) were selected on the date of July 15th, 2004. The trained panels evaluated web sites' contents by the assessment tools using 3-point scale(2:strongly agree, 1:agree, 0:disagree). The contents classified by topics were functional foods(46.4%), cuisine and cooking(38.4%), food sanitation and safety(30.4%) and so on. Operators of web sites were individual(35.9%), company(30.4%) and public institution(33.7%). About 89.5% of web sites were operated for unspecified people. Contents of the web sites were well established especially in consistency in title and contents(1.6), scientific basis of explanations(1.2) and benefit of information(1.2) and so on while not well established in providing relevant sites(0.7), providing contact address and feed back mechanism(0.7) and so on. Web sites operated by public institutions are rated significantly higher than web sites operated by individual or company. In conclusion, in order to qualitatively improve food and nutrition information on the internet, continuing monitoring and evaluation are highly required and web sites operated by public institutions shall be developed further.

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A Study on Removal Request of Exposed Personal Information (노출된 개인정보의 삭제 요청에 관한 연구)

  • Jung, Bo-Reum;Jang, Byeong-Wook;Kim, In-Seok
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.6
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    • pp.37-42
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    • 2015
  • Although online search engine service provide a convenient means to search for information on the World Wide Web, it also poses a risk of disclosing privacy. Regardless of such risk, most of users are neither aware of their personal information being exposed on search results nor how to redress the issue by requesting removal of information. According to the 2015 parliamentary inspection of government offices, many government agencies were criticized for mishandling of personal information and its leakage on online search engine such as Google. Considering the fact that the personal information leakage via online search engine has drawn the attention at the government level, the online search engine and privacy issue needs to be rectified. This paper, by examining current online search engines, studies the degree of personal information exposure on online search results and its underlying issues. Lastly, based on research result, the paper provides a sound policy and direction to the removal of exposed personal information with respect to search engine service provider and user respectively.

Improving the Quality of Web Spam Filtering by Using Seed Refinement (시드 정제 기술을 이용한 웹 스팸 필터링의 품질 향상)

  • Qureshi, Muhammad Atif;Yun, Tae-Seob;Lee, Jeong-Hoon;Whang, Kyu-Young
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.6
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    • pp.123-139
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    • 2011
  • Web spam has a significant influence on the ranking quality of web search results because it promotes unimportant web pages. Therefore, web search engines need to filter web spam. web spam filtering is a concept that identifies spam pages - web pages contributing to web spam. TrustRank, Anti-TrustRank, Spam Mass, and Link Farm Spam are well-known web spam filtering algorithms in the research literature. The output of these algorithms depends upon the input seed. Thus, refinement in the input seed may lead to improvement in the quality of web spam filtering. In this paper, we propose seed refinement techniques for the four well-known spam filtering algorithms. Then, we modify algorithms, which we call modified spam filtering algorithms, by applying these techniques to the original ones. In addition, we propose a strategy to achieve better quality for web spam filtering. In this strategy, we consider the possibility that the modified algorithms may support one another if placed in appropriate succession. In the experiments we show the effect of seed refinement. For this goal, we first show that our modified algorithms outperform the respective original algorithms in terms of the quality of web spam filtering. Then, we show that the best succession significantly outperforms the best known original and the best modified algorithms by up to 1.38 times within typical value ranges of parameters in terms of recall while preserving precision.

Analysis of Execution Behavior for Multprocess-based Web Robots (다중 프로세스 기반 웹 로봇의 수행동작 분석)

  • Kim Hie-Cheol;Lee Yong-Doo
    • Journal of Digital Contents Society
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    • v.2 no.1
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    • pp.9-19
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    • 2001
  • Web robot is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance Web robots are urgently demanded. For this, researches specially geared toward performance scalability of Web robots are required. Hoover, because researches are focused mostly on addressing issues related to commercial implementations, scientific researches and studies are not still made on the performance scalability. In this research, Ive choose a Web robot model implemented by fork-join based. multiprocesses. With respect to the model, we evaluate the effect on the collection efficiency that the timeout values set to requests from Web robots to Web servers have. Also, we analysed the behaviors of Web robots by comparing the execution time between the URL extraction and the uniqueness checking for the extracted URLs. as well as by comparing between the computation time and the network time. Based on the analysis result, we suggest the direction for the design of high performance Web robots.

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Design and Implementation of a High Performance Web Crawler (고성능 웹크롤러의 설계 및 구현)

  • 권성호;이영탁;김영준;이용두
    • Journal of Korea Society of Industrial Information Systems
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    • v.8 no.4
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    • pp.64-72
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    • 2003
  • A Web crawler is an important Internet software technology used in a variety of Internet application software which includes search engines. As Internet continues to grow, implementations of high performance web crawlers are urgently demanded. In this paper, we study how to support dynamic scheduling for a multiprocess-based web crawler. For high peformance, web crawlers are usually based on multiprocess in their implementations. In these systems, crawl scheduling which manages the allocation of web pages to each process for loading is one of the important issues. In this paper, we identify issues which are important and challenging in the crawl scheduling. To address the issue, we propose a dynamic crawl scheduling framework and subsequently a system architecture for a web crawler with dynamic crawl scheduling support. And we analysed the behaviors of Web crawler. Based on the analysis result, we suggest the direction for the design of high performance Web crawler.

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