• Title/Summary/Keyword: Web analytics

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Research Trends Analysis of Big Data: Focused on the Topic Modeling (빅데이터 연구동향 분석: 토픽 모델링을 중심으로)

  • Park, Jongsoon;Kim, Changsik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.15 no.1
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    • pp.1-7
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    • 2019
  • The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

Big Data Analytics Applied to the Construction Site Accident Factor Analysis

  • KIM, Joon-soo;Lee, Ji-su;KIM, Byung-soo
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.678-679
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    • 2015
  • Recently, safety accidents in construction sites are increasing. Accordingly, in this study, development of 'Big-Data Analysis Modeling' can collect articles from last 10 years which came from the Internet News and draw the cause of accidents that happening per season. In order to apply this study, Web Crawling Modeling that can collect 98% of desired information from the internet by using 'Xml', 'tm', "Rcurl' from the library of R, a statistical analysis program has been developed, and Datamining Model, which can draw useful information by using 'Principal Component Analysis' on the result of Work Frequency of 'Textmining.' Through Web Crawling Modeling, 7,384 out of 7,534 Internet News articles that have been posted from the past 10 years regarding "safety Accidents in construction sites", and recognized the characteristics of safety accidents that happening per season. The result showed that accidents caused by abnormal temperature and localized heavy rain, occurred frequently in spring and winter, and accidents caused by violation of safety regulations and breakdown of structures occurred frequently in spring and fall. Plus, the fact that accidents happening from collision of heavy equipment happens constantly every season was acknowledgeable. The result, which has been obtained from "Big-Data Analysis Modeling" corresponds with prior studies. Thus, the study is reliable and able to be applied to not only construction sites but also in the overall industry.

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An Evaluation Method for Web Contents Services (웹콘텐츠 서비스 평가)

  • Jang, Hee S.;Park, Jong T.
    • Journal of Service Research and Studies
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    • v.3 no.2
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    • pp.33-44
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    • 2013
  • As the Internet and mobile services increase, the use of wired/wireless web contents services increase and the demand for various contents explosively grows. To survive in competitive market, and to minimize the errors and warnings for web accessibility and standardization, and then to maximize the web usability, the periodical evaluation for web site should be performed with the events of web marketing and campaign. Through the web evaluation, the errors for technical programming language and contents offering can be found and diagnosed. In this paper, the quantitative and qualitative evaluation method for web site providing web contents are presented, and the analytic results for the 138 home pages in domestic are evaluated to validate the quantitative methodology. The accessibility, standardization, and usability factor are adopted for the evaluation in which accessibility is evaluated for perceivable, operable, understandable, and robust discipline with K-WAH(Korea-Web Accessibility Helper) tool, the standardization are measured for the number of errors and warnings in technical language with the W3C validator, and finally the usability factor is analyzed for the number of visits, average visit duration, and bounce rate with Google Analytics. In addition to, the quantitative analysis is also performed with the consideration of cost for construction and operation of web site. From the results, in the case of total score of 100 in conversion with relative weight, the average and standard deviation are evaluated to be 55 and 14, respectively. The correlation analysis indicates that the coefficient is estimated as 0.058, and then correlation between the quantitative results and cost is evaluated to be a little positive.

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A Study on the Usage Behavior of Public Library Website through an Analysis of Web Traffic (웹 트래픽 분석을 통한 공공도서관 웹사이트 이용행태에 관한 연구)

  • Kang, Munsil;Kim, Seonghee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.32 no.4
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    • pp.189-212
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    • 2021
  • The purpose of this study is to analyze an usage behavior for the public library website through web traffic. For this purpose, using Google Analytics and growth hacking technique, the data of A public library website log was analyzed for three months from August 1, 2021 to October 31, 2021. As a result of the study, the young age group of 18-24 years old and 25-34 years old recorded a high rate of new member registration, & it was found that the inflow rate through SNS was high for external inflows. As a result of analysis for the access rate by time, it was found that the time with the highest inflow rate was between 10 am and 11 am both on Wednesday and Friday. As a access channel, the access rate using mobile (64.90%) was quite high, but at the same time, the bounce rate (27.20%) was higher than the average (24.93%), & the rate of duration time (4 minutes 33 seconds) was lower than thee average (5 minutes 22 seconds). Finally, it was found that the utilization rate of reading program events and online book curation service, which the library focuses on producing and promoting, is very low. These research results can be used as basic data for future improvement of public library websites.

Trusted Fog Based Mashup Service for Multimedia IoT based Smart Environmental Monitoring

  • Elmisery, Ahmed M.;Sertovic, Mirela
    • Journal of Multimedia Information System
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    • v.4 no.4
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    • pp.171-178
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    • 2017
  • Data mashup is a web technology that combines information from multiple sources into a single web application. Mashup applications create a new horizon for new services, like environmental monitoring. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations utilize a data mashup to merge datasets from different Internet of multimedia things (IoMT) context-based services in order to leverage its data analytics performance and the accuracy of the predictions. However, mashup different datasets from multiple sources is a privacy hazard as it might reveal citizens specific behaviors in different regions. The ability to preserve privacy in mashuped datasets and at the same time provide accurate insights becomes a key success for the spread of mashup services. In this paper, we present our efforts to build a fog-based middleware for private data mashup (FMPM) to serve a centralized environmental monitoring service. The proposed middleware is equipped with concealment mechanisms to preserve the privacy of the merged datasets from multiple IoMT networks involved in the mashup application. Also, these mechanisms preserve the aggregates in the dataset to maximize the usability of information to attain accurate analytical results. We also provide a scenario for IoMT-enabled data mashup service and experimentation results.

Key Traffic Metrics as a Basis to Measure Library Performance

  • Udartseva, Olga M.
    • Journal of Information Science Theory and Practice
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    • v.8 no.2
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    • pp.55-67
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    • 2020
  • Webometric research in the Russian library sector is just beginning to gain momentum. This article examines the experience of webometric research in libraries from the perspective of the global practice. In particular, it highlights a number of foreign works, which may have a special practical value for Russian libraries, and emphasizes important webometrics areas for libraries. The purpose of this study is to research the practical application of key performance indicators (KPIs) abroad and conduct a webometric analysis of the websites of some leading Siberian and Far Eastern scientific libraries based on selected KPIs. The study data were collected with SimilarWeb and other analytical tools. The study revealed that key traffic metrics are the basis of webometric research, and identified available promising groundwork for the purpose of their further testing. The shortcomings in the current state of the websites of the Siberian and Far Eastern scientific libraries were noted. Based on the obtained webometric traffic indicators, the ranking of the Siberian and Far Eastern scientific libraries was made.

Impact of Open Access Models on Citation Metrics

  • Razumova, Irina K.;Kuznetsov, Alexander
    • Journal of Information Science Theory and Practice
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    • v.7 no.2
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    • pp.23-31
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    • 2019
  • We report results of selection-bias-free approaches to the analysis of the impact of open access (OA) models on citation metrics. We studied reference groups of Gold and Green OA articles and the group of non-OA (Paywall) articles with the new functionality of the Web of Science Core Collection database, the InCites platform of Clarivate Analytics, and the Dimensions database of Digital Science. For each reference group we obtained the values of the percent of cited articles and citation impact and their dependence on the depth of the citation period. Different research fields were analyzed in two schemas of the InCites platform. We report the higher values and growth rates of the citation metrics: citation impact and %Cited, in the OA reference groups over the Paywall group. The Green OA articles demonstrate the highest values of citation metrics among all the OA models. Dependence of the value of citation impact on citation period follows linear law with R2 values close to 0.9-1.0. The overall annual growth rates of citation impact of the Green OA, Gold OA, and the Paywall articles, k equal, respectively, 3.6, 2.4, and 1.4 in Dimensions and 4.6, 3.6, and 2.3 in the Web of Science Core Collection. We suppose that earlier results reported for the articles in pure OA journals vs. articles in Paywall journals were affected by the high citation impact of the Green and Hybrid OA articles that could not be elucidated in the Paywall journals at that time.

Method for Preference Score Based on User Behavior (웹 사이트 이용 고객의 행동 정보를 기반으로 한 고객 선호지수 산출 방법)

  • Seo, Dong-Yal;Kim, Doo-Jin;Yun, Jeong-Ki;Kim, Jae-Hoon;Moon, Kang-Sik;Oh, Jae-Hoon
    • CRM연구
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    • v.4 no.1
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    • pp.55-68
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    • 2011
  • Recently with the development of Web services by utilizing a variety of web content, the studies on user experience and personalization based on web usage has attracted much attention. Majority of personalized analysis are have been carried out based on existing data, primarily using the database and statistical models. These approaches are difficult to reflect in a timely mannerm, and are limited to reflect the true behavioral characteristics because the data itself was just a result of customers' behaviors. However, recent studies and commercial products on web analytics try to track and analyze all of the actions from landing to exit to provide personalized service. In this study, by analyzing the customer's click-stream behaviors, we define U-Score(Usage Score), P-Score (Preference Score), M-Score(Mania Score) to indicate variety of customer preferences. With the devised three indicators, we can identify the customer's preferences more precisely, provide in-depth customer reports and customer relationship management, and utilize personalized recommender services.

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서비스기반 B2B전자시장의 지속적이용의도에 관한 연구

  • Park, Jae-Seong;Jeong, Gyeong-Ho;Kim, Jae-Jeon;Jo, Geon;Go, Jun
    • 한국경영정보학회:학술대회논문집
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    • 2007.06a
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    • pp.190-197
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    • 2007
  • 급속한 성장세에 있는 서비스기반의 B2B전자시장에 대하여 본 연구에서는 서비스 이용기업의 서비스 지속적이용의도에 영향을 주는 요인을 파악하고, 이들 요인간의 관계를 실증적으로 분석하였다. 실증분석을 위하여 우리나라 대표적인 ASP 방식의 Web analytics 회사의 서비스 이용기업에 대한 실증분석을 실시한 결과 기존채널 교체에 관한 전환비용은 의존도에 유의한 영향을 미쳤고, 신규채널 수용에 관한 전환비용과 사용기간은 의존도에 유의하지 않는 것으로 나타났다. 서비스품질은 ServQual을 사용하여 측정하였으며 이중 신뢰성과 공감성이 만족도에 유의한 영향이 있었지만, 응답성에는 유의하지 않는 것으로 측정되었다. 또한, 만족도는 의존도에 유의하게 나타났고, 만족도와 의존도는 서비스의 지속적이용의도에 유의하였다.

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Issues and Trend of Semantic Web Technologies: from Search to Analytics on Information (정보 검색에서 분석으로의 시맨틱 웹 기술 동향 및 이슈)

  • Jung, Han-Min;Kim, Tea-Jong;Lee, Jin-Hee
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06c
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    • pp.262-265
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    • 2011
  • 본 논문은 영국의 CUBIST, 캐나다의 CTI, 미국의 FUSE, 한국의 InSciTe 및 TOD 프로젝트를 통해 주목 받고 있는 시맨틱 웹 기술 적용 영역의 확장을 다룬다. 특히, 기존 적용 영역이었던 정보 관리와 정보 검색에서 의사 결정과 전략적 기획을 지원할 수 있는 정보 분석으로 무게 중심이 이동하고 있는 현 상황에서 주요한 이슈로 대두되고 있는 개체 간 관계 추적, 추론 검증을 중심으로 한 시맨틱 웹 기술에 의한 작업 자동화를 소개하며, 마지막으로 TOD를 통해 사용자 작업 성능 향상의 필요성과 가치를 높이기 위한 방안들을 살펴본다.