• Convergence Security Journal
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• v.15 no.2
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• pp.19-24
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• 2015

As the Internet usage such as Web3.0, future internet, and internet of things increases, the big data through information exchange between the users and web servers increases. Analyzing those web data, the commercial web sites use the analytic results for marketing and campaign, and non-commercial web sites also use the results to improve the user's services satisfaction. In this paper, the quantitative index is presented to analyze the web sites, and optimized web site design method is also presented through the correlation analysis of index and significance test. From the results for 138 web sites, it is observed that strong plus(+) correlation for visits-unique visitors and page views-average visit duration exists. We also observe the minus(-) correlation between bounce rate and page views per user(or ratio of new visits). In specific, to reduce the bounce rate for users, the strategy to increase the page views and ratio of new visits rather than visits and unique visitors is needed.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Restorative Dentistry and Endodontics
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• v.46 no.3
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• pp.42.1-42.15
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• 2021

Objectives: This study aimed to analyze the main features of the 25 most-cited articles in minimally invasive access cavities. Materials and Methods: An electronic search was conducted on the Clarivate Analytics' Web of Science 'All Databases' to identify the most-cited articles related to this topic. Citation counts were cross-matched with data from Elsevier's Scopus and Google Scholar. Information about authors, contributing institutions and countries, year and journal of publication, study design and topic, access cavity, and keywords were analyzed. Results: The top 25 most-cited articles received a total of 572 (Web of Science), 1,160 (Google Scholar) and 631 (Scopus) citations. It was observed a positive significant association between the number of citations and age of publication (r = 0.6907, p < 0.0001); however, there was no significant association regarding citation density and age of publication (r = -0.2631, p = 0.2038). The Journal of Endodontics made the highest contribution (n = 15, 60%). The United States had the largest number of publications (n = 7) followed by Brazil (n = 4), with the most contributions from the University of Tennessee and Grande Rio University (n = 3), respectively. The highest number of most-cited articles were ex vivo studies (n = 16), and 'fracture resistance' was the major topic studied (n = 10). Conclusions: This study revealed a growing interest for researchers in the field of minimally invasive access cavities. Future trends are focused on the expansion of collaborative networks and the conduction of laboratory studies on under-investigated parameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.3
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• pp.1014-1025
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• 2020

Cloud computing services changed the way the data are managed across the healthcare system that can improve patient care. Currently, most healthcare organizations are using cloud-based applications and related services to deliver better healthcare facilities. But architecting a cloud-based healthcare system needs deep knowledge about the working nature of these services and the requirements of the healthcare environment. The success is based on the usage of appropriate cloud services in the architecture to manage the data flow across the healthcare system.Cloud service providers offer a wide variety of services to ingest, store and process healthcare data securely. The top three public cloud providers- Amazon, Google, and Microsoft offers advanced cloud services for the solution that the healthcare industry is looking for. This article proposes a framework that can effectively utilize cloud services to handle the data flow among the various stages of the healthcare infrastructure. The useful cloud services for ingesting, storing and analyzing the healthcare data for the proposed framework, from the top three cloud providers are listed in this work. Finally, a cloud-based healthcare architecture using Amazon Cloud Services is constructed for reference.

• Smart Media Journal
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• v.12 no.10
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• pp.38-46
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• 2023

Farming activities are transforming from traditional skill-based agriculture into knowledge-based and technology-driven digital agriculture. The use of intelligent information and communication technology introduces the idea of smart farming that enables farmers to collect weather data, monitor crop growth remotely and detect crop diseases easily. The introduction of Plantix, a pest and disease management tool in the form of a mobile application has allowed farmers to identify pests and diseases of the crop using their mobile devices. Hence, this study collected the reviews of Plantix to explore the response of the users on the Google Play Store towards the application through Latent Dirichlet Allocation (LDA) topic modeling. Results indicate four latent topics in the reviews: two positive evaluations (compliments, appreciation) and two suggestions (plant options, recommendations). We found the users suggested the application to additional plant options and additional features that might help the farmers with their difficulties. In addition, the application is expected to benefit the farmer more by having an early alert of diseases to farmers and providing various substitutes and a list of components for the remedial measures.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• International Commerce and Information Review
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• v.13 no.1
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• pp.3-28
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• 2011

Recently marketing methods of small and medium exporting firms have changed from internet marketing using homepage, or e-catalogs, to search engine marketing. However, there is no specific proof of search engine marketing effectiveness. Therefore the purpose of this research is to explore marketing performance of search engine marketing(SEM) based on search engine optimization. In order to build an optimal SEM strategy, quantitative data are collected from the Google-analytics such as homepage visits, page views, and traffic source for three years. At the same time, this study has carried out a survey to measure the qualitative effectiveness. The result of this quantitative study suggests that the existing carryover effects and lag effects would be maintained through search engine optimization. Meanwhile, the qualitative survey shows that satisfaction and awareness of homepage have been improved after search engine optimization. This can support logically increase of homepage visiting ratio of quantitative analysis. Also exporting companies know very well, that traffic and page views have increased after search engine optimization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.155-161
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• 2021

Gesture recognition analytics through a camera in real time have been widely studied in recent years. Since a small number of features from human joints are extracted, low accuracy of classifying models is get in conventional gesture recognition studies. In this paper, CBAM (Convolutional Block Attention Module) with high accuracy for classifying images is proposed as a classification model and algorithm calculating the angle of joints depending on actions is presented to solve the issues. Employing five exercise gestures images from the fitness posture images provided by AI Hub, the images are applied to the classification model. Important 8-joint angles information for classifying the exercise gestures is extracted from the images by using MediaPipe, a graph-based framework provided by Google. Setting the features as input of the classification model, the classification model is learned. From the simulation results, it is confirmed that the exercise gestures are classified with high accuracy in the proposed model.

• Journal of Information Science Theory and Practice
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• v.6 no.4
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• pp.6-16
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• 2018

This article shows an approach to the study of two fundamental aspects of the prepublication of scientific manuscripts in specialized repositories (arXiv). The first refers to the size of the interaction of "standard papers" in journals appearing in the Web of Science (WoS)-now Clarivate Analytics-and "non-standard papers" (manuscripts appearing in arXiv). Specifically, we analyze the citations found in the WoS to articles in arXiv. The second aspect is how publication in arXiv affects the citation count of authors. The question is whether or not prepublishing in arXiv benefits authors from the point of view of increasing their citations, or rather produces a dispersion, which would diminish the relevance of their publications in evaluation processes. Data have been collected from arXiv, the websites of the journals, Google Scholar, and WoS following a specific ad hoc procedure. The number of citations in journal articles published in WoS to preprints in arXiv is not large. We show that citation counts from regular papers and preprints using different sources (arXiv, the journal's website, WoS) give completely different results. This suggests a rather scattered picture of citations that could distort the citation count of a given article against the author's interest. However, the number of WoS references to arXiv preprints is small, minimizing this potential negative effect.

• Clinics in Shoulder and Elbow
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• v.26 no.1
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• pp.55-63
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• 2023

Background: Common questions about shoulder arthroplasty (SA) searched online by patients and the quality of this content are unknown. The purpose of this study is to uncover questions SA patients search online and determine types and quality of webpages encountered. Methods: The "People also ask" section of Google Search was queried to return 900 questions and associated webpages for general, anatomic, and reverse SA. Questions and webpages were categorized using the Rothwell classification of questions and assessed for quality using the Journal of the American Medical Association (JAMA) benchmark criteria. Results: According to Rothwell classification, the composition of questions was fact (54.0%), value (24.7%), and policy (21.3%). The most common webpage categories were medical practice (24.6%), academic (23.2%), and medical information sites (14.4%). Journal articles represented 8.9% of results. The average JAMA score for all webpages was 1.69. Journals had the highest average JAMA score (3.91), while medical practice sites had the lowest (0.89). The most common question was, "How long does it take to recover from shoulder replacement?" Conclusions: The most common questions SA patients ask online involve specific postoperative activities and the timeline of recovery. Most information is from low-quality, non-peer-reviewed websites, highlighting the need for improvement in online resources. By understanding the questions patients are asking online, surgeons can tailor preoperative education to common patient concerns and improve postoperative outcomes. Level of evidence: IV.